{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 通过量子神经网络对鸢尾花进行分类\n",
    "\n",
    "[![下载Notebook](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/master/resource/_static/logo_notebook.svg)](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/notebook/master/mindquantum/zh_cn/case_library/mindspore_classification_of_iris_by_qnn.ipynb)&emsp;\n",
    "[![下载样例代码](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/master/resource/_static/logo_download_code.svg)](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/notebook/master/mindquantum/zh_cn/case_library/mindspore_classification_of_iris_by_qnn.py)&emsp;\n",
    "[![查看源文件](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/master/resource/_static/logo_source.svg)](https://gitee.com/mindspore/docs/blob/master/docs/mindquantum/docs/source_zh_cn/case_library/classification_of_iris_by_qnn.ipynb)\n",
    "\n",
    "## 概述\n",
    "\n",
    "量子神经网络是一类将人工神经网络与量子计算相结合的算法。在经典神经网络中，人们以类似人脑神经系统的网状结构作为计算模型，对特定问题进行预测，并根据真实结果对神经元的参数进行优化，反复迭代直到模型能较为准确的预测结果。而在量子线路中，我们同样可以搭建出类似的网状结构，并将其中一些含参数的门作为神经元，然后我们可以测量出相关哈密顿量的期望值作为损失函数，对门参数进行优化，直到找出最优参数。这样，我们就训练出了一个量子神经网络。量子并行性或量子纠缠有可能为量子神经网络带来额外的优势，但目前还没有证据表明量子神经网络相比经典神经网络具有优越性。一个典型的量子神经网络包含 Encoder（编码层）和 Ansatz（训练层），Encoder 可以将经典数据编码到量子态中，常见的编码方式有振幅编码、相位编码和IQP编码等。Ansatz可以根据输入给出预测结果，常见的 Ansatz 有 [Hardware Efficient Ansatz](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/nisq/mindquantum.algorithm.nisq.HardwareEfficientAnsatz.html)、[Strongly Entangling Ansatz](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/nisq/mindquantum.algorithm.nisq.StronglyEntangling.html) 等。\n",
    "\n",
    "在之前的案例中，我们介绍了什么是变分量子线路，并通过一个简单的例子体验了如何搭建量子神经网络来解决一个小问题。在本文档中，我们将体验升级，将会介绍如何通过搭建量子神经网络来解决经典机器学习中的问题。我们选取的问题是：监督学习中的鸢尾花分类问题。\n",
    "\n",
    "问题描述：鸢尾花（iris）数据集是经典机器学习中常用的数据集，该数据集总共包含150个样本（分为3种不同的亚属：山鸢尾（setosa）、杂色鸢尾（versicolor）和维吉尼亚鸢尾（virginica），每个亚属各有50个样本），每个样本包含4个特征，分别为花萼长度（sepal length）、花萼宽度（sepal width）和花瓣长度（petal length）、花瓣宽度（petal width）。\n",
    "\n",
    "我们选取前100个样本（山鸢尾（setosa）和杂色鸢尾（versicolor）），并随机抽取80个样本作为训练集，通过搭建量子神经网络对量子分类器（Ansatz）进行训练，学习完成后，对剩余的20个样本进行分类测试，期望预测的准确率尽可能高。\n",
    "\n",
    "思路：我们需要将100个样本进行划分，分成80个训练样本和20个测试样本，根据训练样本的经典数据计算搭建Encoder所需的参数，然后，搭建Encoder，将训练样本的经典数据编码到量子态上，接着，搭建Ansatz，通过搭建的量子神经网络层和MindSpore的算子对Ansatz中的参数进行训练，进而得到最终的分类器，最后，对剩余的20个测试样本进行分类测试，得到预测的准确率。\n",
    "\n",
    "## 环境准备\n",
    "\n",
    "首先，我们需要导入鸢尾花的数据集，而在导入该数据集前，我们需要使用sklearn库中的datasets模块，因此读者需要检查是否安装了sklearn库，可执行如下代码进行安装。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```bash\n",
    "pip show scikit-learn\n",
    "```"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "若无报错，则表明已安装。简单说明一下，sklearn是scikit-learn的简称，是一个基于Python的第三方模块。sklearn库集成了一些常用的机器学习方法，在进行机器学习任务时，并不需要实现算法，只需要简单的调用sklearn库中提供的模块就能完成大多数的机器学习任务。\n",
    "\n",
    "若未安装sklearn库，则可通过运行如下代码来安装。"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "```bash\n",
    "pip install scikit-learn\n",
    "```"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 安装 mindquantum\n",
    "!pip install mindquantum -i https://pypi.mirrors.ustc.edu.cn/simple"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(150, 4)\n",
      "['sepal length (cm)', 'sepal width (cm)', 'petal length (cm)', 'petal width (cm)']\n",
      "['setosa' 'versicolor' 'virginica']\n",
      "[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 2\n",
      " 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2\n",
      " 2 2]\n",
      "(150,)\n"
     ]
    }
   ],
   "source": [
    "import numpy as np                                        # 导入numpy库并简写为np\n",
    "from sklearn import datasets                              # 导入datasets模块，用于加载鸢尾花的数据集\n",
    "\n",
    "iris_dataset = datasets.load_iris()                       # 加载鸢尾花的数据集，并存在iris_dataset\n",
    "\n",
    "print(iris_dataset.data.shape)                            # 打印iris_dataset的样本的数据维度\n",
    "print(iris_dataset.feature_names)                         # 打印iris_dataset的样本的特征名称\n",
    "print(iris_dataset.target_names)                          # 打印iris_dataset的样本包含的亚属名称\n",
    "print(iris_dataset.target)                                # 打印iris_dataset的样本的标签的数组\n",
    "print(iris_dataset.target.shape)                          # 打印iris_dataset的样本的标签的数据维度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上述打印可以看到，该数据集共有150个样本，每个样本均有4个特征，分别为花萼长度（sepal length）、花萼宽度（sepal width）和花瓣长度（petal length）、花瓣宽度（petal width）。同时样本包含3种不同的亚属：山鸢尾（setosa）、杂色鸢尾（versicolor）和维吉尼亚鸢尾（virginica），每个样本有对应的分类编号，0表示样本属于setosa，1表示样本属于versicolor，2表示样本属于virginica，因此有一个由150个数字组成的数组来表示样本的亚属类型。\n",
    "\n",
    "由于我们只选取前100个样本，因此执行如下命令。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100, 4)\n",
      "['sepal length (cm)', 'sepal width (cm)', 'petal length (cm)', 'petal width (cm)']\n",
      "['setosa' 'versicolor']\n",
      "[0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
      " 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1\n",
      " 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1]\n",
      "(100,)\n"
     ]
    }
   ],
   "source": [
    "X = iris_dataset.data[:100, :].astype(np.float32)         # 选取iris_dataset的data的前100个数据，将其数据类型转换为float32，并储存在X中\n",
    "X_feature_names = iris_dataset.feature_names              # 将iris_dataset的特征名称储存在X_feature_names中\n",
    "y = iris_dataset.target[:100].astype(int)                 # 选取iris_dataset的target的前100个数据，将其数据类型转换为int，并储存在y中\n",
    "y_target_names = iris_dataset.target_names[:2]            # 选取iris_dataset的target_names的前2个数据，并储存在y_target_names中\n",
    "\n",
    "print(X.shape)                                            # 打印样本的数据维度\n",
    "print(X_feature_names)                                    # 打印样本的特征名称\n",
    "print(y_target_names)                                     # 打印样本包含的亚属名称\n",
    "print(y)                                                  # 打印样本的标签的数组\n",
    "print(y.shape)                                            # 打印样本的标签的数据维度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上述打印可以看到，此时的数据集`X`中只有100个样本，每个样本依然有4个特征，仍为花萼长度（sepal length）、花萼宽度（sepal width）和花瓣长度（petal length）、花瓣宽度（petal width）。此时只有2种不同的亚属：山鸢尾（setosa）和杂色鸢尾（versicolor），并且每一个样本有对应的分类编号，0表示它属于setosa，1表示它属于versicolor，因此有一个由100个数字组成的数组来表示样本的亚属类型。\n",
    "\n",
    "## 数据图像化\n",
    "\n",
    "为了更加直观地了解这100个样本组成的数据集，我们画出所有样本不同特征之间组成的散点图，执行如下命令。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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bcnVK1/G6zuolq+tg8kG3M00tJouql6rudX0xxWIUbg3XBdsFt2Xshj3gbQkAAIIfywIDQD5jGIa6zeimfSf3SZIrEZq+jNSYVWP06a+f5qjOvSf3qufMnrpgu+CqL73uC7YL6jWrl/ad2pcn8V+Je765Rz8d+EmSXAPw9M89Z+ccjVoxKmCxAQAAAEBu/K/Z/2QxWdyetzlsGtx4sB8jymxc53HZlqlVupZKRpT0us57m97rcQlfu2HXvU3v9bq+iJAI/bfBf2U1u58rYjFZ9N8G//W6TgAAgNwguQoA+cyyvcu07dg22Yys9+QxyaSEnxJkGJ6XQ7rcxI0TZXPYslxCyZChNHuaJm2clOuY88LB5IOauX2m28G3IUPvrH9HZy+e9XNkAAAAAJB7D7d6WDVL13SbYH2y7ZOqXaa2n6PKqGbpmrql9i1uz5tNZn32n89yVGevWr3UvXp3mU2Zbz+aTWZ1r95dPWv2zFGdozuMVtmiZWU1ZUywmuTc3uONrm+oVESpHNUJAACQUyRXASCf+WH3Dx6fxDVkaOffO3X07FGv6/zmj2+yfWL4611f5yjOvLbkryXZ7p9z5uIZrTu8zk8RAQAAAMCViwqL0k+DftKgxoMUZglzHa8QVUHv3viuEjol5KreMxfP6PXVr6vmOzVVbGwxVRpfSaNXjNbxc8dzVd/c2+bqjvp3yPyv24Ulw0vq57t+VpO4Jjmqz2K26Is+X6hfvX4ZxrhWs1X96vXTl32+lMXsfkZvVspFltO6Iet0S51bMtRZrWQ1fX7L53qgxQM5qg8AACA32HMVAPIZm8PmeurWkzR7mtd1elM2J/X5Qvryv9kJdJwIkB9/lCZMkFavlkJCpO7dpQcekGrUCHRkAAAAQLZKFCmhqT2m6rXrXtMfJ/5QmDVMdcvUzXFyMd2JcyfUfnp7/Xb8N9fWL2eTz2rMqjF6f8v7+mnQT6pUvFKO6lxzcI2+/P1LmU1mV51mmfXPhX/04qoXNa/PPIVYQnJU54T1E/Tptk9l0aXPaRiGPt32qZrENdEjrR/JUX2SMyk989aZOn7uuP46+ZeKhRZT7dK1ZTJlP44GAADIC8xcBYB8pnn55kpzeE4gxhSNUbnIcl7X2Sa+jcfZsFazVW0rtvW6Pl9oXr55tmUsJosaxTbyfTDIX158UbrmGunLL6VDh6S9e6WJE6V69aQFCwIdHQAAAOC16PBoNS/fXA1iGuQ6sSpJD37/oH4//rsrCZrObtiVdDpJ/b/sn6P6Um2p6jmzp87bzmfYosYhZ/3f7/5er61+LUd1bji8QY8uetQZly6tpJS+qtLwRcO16cimHNV5udIRpdWifAvVKVOHxCoAAPArkqsAkM/cUvsWlSpSKst9aSTn3jQPtngwRwPxB1o84HFmqM1h09DmQ3Mca15qFNtIrcq3cpsEtpgs6l2nt2KKxfg5MgTUokXSyJHOr22X/R222ZyvW2+VkpICExsAAAAQAEfPHNXsHbPdbv1iM2z6+eDP2nZ0m9d1zvt9nv4+93emZG06h+HQ2+vflt3hfruZf3t3w7vZPuQ7YcMEr+sDAADIL0iuAkA+E2YN0/zb5yvMEpZhIJq+703nqp31eNvHc1Rni/It9HLnlyVJVtOlOi0mZ4L2lc6veDVz1Nc+u+UzlYko44orndlkVvVS1TXhRgbehc748ZLFzYMEhiGlpUnvv+/XkAAAAIBA2pK0xW1i9XLrDq/zus51h9YpxOx5yd+kM0k6cvqI13X+dOCnbB/y/Wn/T17XBwAAkF+QXAWAfKhdxXb65X+/6N6m96pUkVIKt4arQWwDTek+RQv6LlCoJTTHdT7R9gktuWOJulbrqqIhRVU0pKhuqH6DltyxJMfJWl+pWqKqtv5vq56++mmVjyyvcGu4qpaoqoROCVo3ZJ1KRZQKdIjwt1WrJLuHG0cOh7Rypf/iAQAAAALM02zQ3JRLL2vIyNM6vdmf1Wrxvj4AAID8gt9gACCfSp+pmZezNTtV7aROVTvlWX2+ULZoWb3Q8QW90PGFQIeC/MCbvZPMPCsGAACAwqNl+ZaKCInQubRzbsuYZFKnKt6P/bpc1UWvrXG/p6pJJtUqXUuxxWK9rrNb9W7688SfbmfZWkwW9ajRw+v6AAAA8gvuRgIAgPzr2mslq4dnwcxmZxkAAACgkIgMi9TQ5kNlUtYPIlpMFt1W9zbFR8d7XWenqp1Ut0zdDNvIXM6QoafaPSWTNw8//r/7m98vi9mSZZwmmWQ1W3Vfs/u8rg8AACC/ILkKAADyr+HDJZubfZrMZik8XLrrLv/GBAAAAATYi9e+qJtr3yzJmUyVJLPJeZuvdXxrTe0xNUf1mU1mfdvvW1UsXjFDXenLAI9oN0J3NLgjR3VWLVFV8/rMU5g1LNO5MGuYvuzzpaqUqJKjOtMZhqGV+1Zq8sbJ+uzXz3Ty/Mlc1QMAAJAbLAsMAHnAYTi0aM8ifbD5A+1P3q+YYjEa2HCgetXqlaM9aS539uJZfbbtM83ZOUcpF1JUt2xd/a/Z/9SifIs8jh7Ix9q3l956Sxo2zDmDNT3RarFIoaHSN99IZcoENkYAAADAz0ItoepTp4+W7V2mUxdOSXKOSyOsEepTt48iwyJzXGel4pW0/b7tmrVjlnMcmpqiemXq6d5m96pRbKNcxfn3mb91wXYh0/ELtgv6+8zfuapz9cHVGjh/oHb/s9t1LMwSpmEth2lsp7GymC25qhcAAMBbJsMwst+tHpKklJQURUdHKzk5WVFRUYEOB0A+kWpLVe85vfXNH9/IYrLIbthd/29VoZV+6P+DosOjc1Tn3pN71eGjDjqQfEAmmWTIkNVslc1h02OtH9Mr172So+WYkLfoD3Luitvsl1+k996Tfv5ZCgmRevSQ7rlHqlAh74MFAPgMfWjO0WYAsjL/9/n6z6z/yFDWt/Xeu/E93dc8sEvubk3cqsZTGnsss+WeLWoU18jrOn9J+kWtPmili/aLchiODOdMMum+5vfp3RvfzU24+R79Qc7RZgAAyTf9AcsCA8AVenrp0/r2z28lSXbDnuH/Gw5v0JBvhuSoPofh0I0zbtSRlCOS5Bos2xzOGXuvrXlN07dOz4vQgYKjYUNp8mRp+3ZpyxbphRdIrAIAAKBQMgxDjy561GOZEUtH6HzaeT9FlLVOH3fKtkznTzrnqM5RK0YpzZ6WKbEqOcfOEzdM1N6Te3NUJwAAQE6RXAWAK5CSmqKJGydmObCTnEnWL3Z+of2n9ntd5+I9i/X78d9lM7LeZ9Ikk8b9PE4sPAAAAAAAhc+GIxv018m/3M5alaTk1GT9sPsHP0aV2T8X/sm2zInzJ7yuL/lCsr754xvXw8xZMZvMmrFthtd1AgAA5AbJVQC4AusOrdN5m+engQ0ZWr5vudd1Lv5rscd9Wg0Z+uPEH0o6k+R1nQAAAACA4PD3We/2Kj129piPI/Gvf87/4/bB5nRmkznoPjcAAMh/SK4CwBXw9MTs5dKX9PWqToddJmW/n2pO6gQAAAAABIf46Pg8LVdQlClaRiHmEI9l7IY96D43AADIf0iuAsAVaBLXxOMs03StK7T2us5WFVopzZHmsUy5yHIqF1nO6zoBuLFzp/Ttt9KaNZLD81PwAAAAQH5Qv2x9NYhpILPJ/W29skXLqstVXfwYVWblI8tnWyY+yvtEaLHQYupTr4/HMbhJJv23wX+9rhMAACA3SK4CwBUoW7Ssbq97uywmS5bnrWarrql4jeqWret1nTfXvlkxRWPc1mmSScNaDpPFnPV5AF7YsEFq0UKqW1fq3l1q00aqUkWaOTPQkQEAAAAemUwmTbhhgswmc6YEq+n//3v3xne9ehDYlzYM3pBtmXV3rctRnaM7jFZUaJTb8fLzHZ5XbLHYHNUJAACQUyRXAeAKvXPjO6pXtp5rEJvObDKrXGQ5ffqfT3NUX6glVF/3/VoRIREZBozpg+abat6k4a2H503wKPTGjRsnk8mkhx9+2GO5OXPmqFatWgoPD1f9+vX13Xff+SdAX9i0SbrmGmnz5ozHDxyQ+vaVpk0LTFwAAAAIasv2LtN/Zv1HFd+sqOrvVNeTi5/U/lP7c1XX1ZWu1g/9f8g0O7RURCl9fsvnurXOrbmqd/vR7br2o2sV9mKYrC9YVeaVMnpm2TNy5GKVl7joOK0fsl7mLG4/mmXWlnu2KC46Lkd1Vi1RVWuGrFH7yu0zHC9btKwm3DBBz1z9TI7jBAAAyCmSqwBwhYqHF9fPd/2st65/S3XL1FV0WLSqlaymFzu+qK33bs3Vfi8tyrfQtvu26ZFWj6h8ZHkVDy+uluVb6tObP9UXt30R8CeQERw2bNigyZMnq0GDBh7LrV69Wn379tXgwYO1ZcsW9erVS7169dL27dv9FGkeGz5cSkuT7G72TH7kEencOf/GBAAAgKBlGIaeXPykOn3cSd/88Y0OphzU7n926/U1r6v2u7W1Yt+KHNd5OvW0nl3+rA6mHMzwkO+Jcyf03IrndPTM0RzXOXfnXDWY1EDL9y3XRftF2Q27jp8/rrE/jtVVb1+li7aLOa6zefnmso+ya8HtC9Q0rqmaxjXVgtsXyD7KrkZxjXJcnyTVKFVDSwcs1Z6H9ui7ft9p1Z2rdOiRQxraYqhMJlP2FSBg3n33XVWuXFnh4eFq2bKl1q9f77H8+PHjVbNmTRUpUkTx8fF65JFHdOHCBT9FCwCAeybDMIxAB1FQpKSkKDo6WsnJyYqKigp0OACAAAmG/uDMmTNq0qSJ3nvvPb344otq1KiRxo8fn2XZPn366OzZs1qwYIHrWKtWrdSoUSNNmjTJq/fLN222b59z+d/szJjhnMUKAMhT+aY/KEBoM6Dgm7tzrnrP6Z3lObPJrKIhRXXwkYOKDo/2us4hXw/R9K3TZTcyPzBoNVvVsXJHLbpjkdf1XbBdULGxxbKsL93NtW7Wl32+9LpO5K2C3h/MmjVLAwYM0KRJk9SyZUuNHz9ec+bM0a5du1S2bNlM5WfMmKG77rpL06ZNU5s2bfTHH3/ozjvv1O2336433njDq/cs6G0GAMgbvugPmLkKAEAhNHToUHXr1k2dO3fOtuyaNWsylevatavWrFnj9prU1FSlpKRkeOULhw5lX8ZikQ4e9H0sAAAAKBTeWPOG2z1CHYZDZy6e0ce/fOx1fSfOndDHv3zsNhFqc9i0+K/F2nV8l9d1jlo+ymNiVZK+3vW1bA6b13UCl3vjjTd09913a9CgQapTp44mTZqkiIgITXOzLcvq1avVtm1b9evXT5UrV1aXLl3Ut2/fbGe7AgDgDyRXAQAoZGbOnKnNmzcrISHBq/JJSUmKiYnJcCwmJkZJSUlur0lISFB0dLTrFR+f8+WxfaJMmezL2O1SFk9OAwAAADnlMBxae2itx8SlSSb9eOBHr+vceGSj0hxp2Zb76cBPXte55K8l2ZaxG3ZtSdzidZ1AuosXL2rTpk0ZHto1m83q3Lmz24d227Rpo02bNrmSqX/99Ze+++473XjjjW7fJ98+5AsACDokVwGgENnzzx49tugxNZrUSI0mNdJjix7Tnn/2BDos+NHBgwc1bNgwffbZZwoPD/fZ+4wYMULJycmu18H8MhO0Zk2pcWPJ7OFXoPBw6eab/RcTAAAAglq2+4CavCiTk/pyWM5XdQLpjh8/LrvdnqOHdvv166cXXnhB7dq1U0hIiK666ip16NBBTz/9tNv3ybcP+QIAgk6BTq4ePnxY//3vf1WqVCkVKVJE9evX18aNG92WX7FihUwmU6aXp5k3ABAsZu+YrVrv1tL4teP1y9Ff9MvRXzR+7XjVereW5uyYE+jw4CebNm3SsWPH1KRJE1mtVlmtVq1cuVJvv/22rFar7PbMT9THxsbq6NGjGY4dPXpUsbGxbt8nLCxMUVFRGV75xquvOv/v7sbQqFFStPf7XQEAAADumE1mtavYzu2ywJJkGIY6Vu7odZ0tyrdQmCUs23LtK7X3us4bqt2QbRmr2aomsU28rhO4EitWrNDYsWP13nvvafPmzfryyy/17bffasyYMW6vybcP+QIAgk6BTa6ePHlSbdu2VUhIiL7//nvt3LlTr7/+ukqUKJHttbt27VJiYqLrldWm6QAQTHYd36X+X/aXzWHLsByV3bDL5rCp35f99MeJPwIYIfylU6dO2rZtm7Zu3ep6NWvWTP3799fWrVtlsWS+6dO6dWstXbo0w7HFixerdevW/go7b3XqJH3zjVSuXMbjxYo5E69PPhmYuAAAABCUHm39qNtlgc0ms4qHF1f/+v29rq94eHHd1fgumU1Z39azmCzqXr27rip5ldd1jrxmpKxmq8cyt9a+VWZPK8AAbpQuXVoWiyVHD+2OHDlSd9xxh4YMGaL69evr5ptv1tixY5WQkCCHw5HlNfn6IV8AQFDx/FtTPvbyyy8rPj5eH374oetYlSpVvLq2bNmyKl68uI8iA4D8590N73ouYEjvrn9Xb93wln8CQsBERkaqXr16GY4VLVpUpUqVch0fMGCAypcv79qTddiwYWrfvr1ef/11devWTTNnztTGjRs1ZcoUv8efZ268Udq/X1q6VNq7VypVSrrhBqlo0UBHBgAAgCBzU82bNLrDaI1aMUpWs1U2h02SM7FaNKSovu33rSLDInNU5+tdXtfvx3/X8n3LZZJJhgzXubpl62p6r+k5qi/UGqqvbv9KPWb0kEOZE1e1StfSZ//5LEd1AulCQ0PVtGlTLV26VL169ZIkORwOLV26VA888ECW15w7dy5TMj/9YWDDMLK6BAAAvymwj5t9/fXXatasmXr37q2yZcuqcePGmjp1qlfXNmrUSHFxcbruuuv0888/uy3HJugAgsXCPQtdA/is2AybFu5Z6MeIkJ8dOHBAiYmJru/btGmjGTNmaMqUKWrYsKHmzp2r+fPnZ0rSFjgWi9Sli3TvvdKtt5JYBQAAgM881/45rR28Vv3q91Pt0rXVOLaxnm//vP548A+1js/5ijBFQoqoU5VOspgsGRKrJpnUNr6tSkWUynGdN1a/Ubsf2q2batykoiFFFWoOVYXICnrtute0474dzFrFFRk+fLimTp2qjz76SL/99pvuu+8+nT17VoMGDZLkfMh3xIgRrvI9evTQxIkTNXPmTO3du1eLFy/WyJEj1aNHjyxXXAIAwJ8K7MzVv/76SxMnTtTw4cP19NNPa8OGDXrooYcUGhqqgQMHZnlNXFycJk2apGbNmik1NVXvv/++OnTooHXr1qlJk8x7RiQkJGj06NG+/igA4HPePNXpMLJeVgfBb8WKFR6/l6TevXurd+/e/gkIAAAACEItK7RUywot86SuV35+Rc8ufzbTcUOGJm6cKMMwNLH7xBzXW6VEFX3V96u8CBHIoE+fPvr777/13HPPKSkpSY0aNdIPP/ygmJgYSc6HfC9P4D/77LMymUx69tlndfjwYZUpU0Y9evTQSy+9FKiPAACAi8kooOsohIaGqlmzZlq9erXr2EMPPaQNGzZozZo1XtfTvn17VaxYUZ988kmmc6mpqUpNTXV9n5KSovj4eCUnJ7NmP4AC5e5v7tb0rdPdzl61mq0a3HiwJnWf5OfICqaUlBRFR0fTH+QAbQYAkOgPcoM2A/BvDodDRcYW0UX7RbdlTDIpZUSKioUW82Nk8CX6g5yjzQAAkm/6gwK7nkdcXJzq1KmT4Vjt2rV14MCBHNXTokUL7d69O8tzbIIOIFg80PwB2R12t+ftDruGNh/qx4gAAAAAALkxa8csj4lVyTmD9eWfXvZTRAAAAIVLgU2utm3bVrt27cpw7I8//lClSpVyVM/WrVsVFxeXl6EBQL7TMLahJnefLJNMspovrQhvNVtlkklTekxR/Zj6AYwQQJYOHJB695bi4qTYWOn666UdOwIdFQAAAAJo1/Fd2ReS9NfJv3wcCQAAQOFUYPdcfeSRR9SmTRuNHTtWt912m9avX68pU6ZoypQprjIjRozQ4cOH9fHHH0uSxo8frypVqqhu3bq6cOGC3n//fS1btkyLFi0K1McAAL+5u+ndalquqd5Z946W7F0iSepctbMebPGgmsRl3ncaQIC9/750zz3S5Ts4LFzofI0cKb3wQuBiAwAAQMBUK1nNq3KViudsAgIAAAC8U2CTq82bN9e8efM0YsQIvfDCC6pSpYrGjx+v/v37u8okJiZmWCb44sWLevTRR3X48GFFRESoQYMGWrJkiTp27BiIjwAAftckrok+7PVhoMMAkJ3ffpPuvtv9+TFjpFatpBtv9F9MAAAAyBf61e+nu76+S2mONLdlTDLpqbZP+TEqAACAwqPAJlclqXv37urevbvb89OnT8/w/RNPPKEnnnjCx1EBAABcoUceyb7Mk0+SXAXwf+zdd1xTZxfA8d9NwhAUnODAvfe2jrpQ66i7rrpHnXV3+NpltXW0WmvrrNY6qlZb665KXah14sC9FfdEBQUFktz3jxQqQiCBQAKcbz98qvc+9+QQax9yz33OI4QQIgPSaDR8Uf8LPt/1udkxvSv1xsPVIxWzEkIIIYTIONJ0cVUIIYQQIl3avz/xMWfPpnweQgghhBDCZgLvBTInYA4BdwLIpMtEm5Jt6FelHzndclod67N6nxEeGc6UfVNQUWOd61WxF7+0+cVWaSfbtSfXmHdkHjuv7QSgUZFGDKo2iEJZC9k3MSGEEEKIJJLiqhBC2ECUIYrfz/zOgmMLuB5yHW93b/pU6kOPij1wc3Kzd3oxzjw4w+yA2ey4ugMwfah9v/r7lPUqa+fMhBCxGAyJj1HVxMcIIYQQQgiH8O2+bxmzfQw6jQ69UQ/AoduHmLJvCtt6bKNa3mpWxXv68ikLji2IU1gF+OPsH4xvMN4h9lz98+yfvPvnuxhVIwbV9DPu8XvHmX5gOis7rKR96fZ2zlAIIYQQwnoaeycghBBpXVhkGL5Lfem+tjt7b+wl6GkQh28fZvBfg6m+oDoPwx7aO0UAfj3xKxXmVWDBsQVcfHyRi48vsuDYAirMq8Cyk8vsnZ4Q4lVFiiQ+JleulM9DCCGEEEIk2+ZLmxmzfQxATGEVwKgaeRbxjGbLmhEWGWZVzAaLG/DoxaN4z4VHhVNrYa2kJ2wjF4Mv0uXPLuiN+pjCKoBBNaA36um8ujOXgi/ZMUMhhBBCiKSR4qoQQiTT6L9Hs/+mqYWnUTUCoP77z4VHF+i5rqc90wNMK1Z7r++NUTXG+jCvN+oxqkZ6revF2YfSYlQIhzFhQuJjhg9P+TyEEEIIIUSyTd0/Fa2ijfecQTUQ/CKY5aeWWxzvRsgNTtw/keCYu8/vsidoj1V52trsw7NBJd7VtarpBLMDZtshMyGEEEKI5JHiqhBCJMPjF49ZHLg4pqj6OoNqYOvlrXZ/Gnd2wGw0ivn/5WsUjemDrxDCMbRrZ/oyp1o1+PTT1MtHCCGEEEIkiVE1suf6nlgrN1+nUTQx+5FaYsWpFRaNW3xiscUxU4LfFT/0qt7seb2qZ+vlramYkRBCCCGEbUhxVQghkuHInSNEGiITHbf3xt5UyMa8HVd3xFqx+jq9Uc/2a9tTMSMhRKLWrIFp02K3//X0hI8/hkOH7JeXEEIIIYSwmKqqqGrclZuvM/fAbnwMRvOF2qTGTAmWvL69cxRCCCGESAoprgohhBBCOKoPPoAHD0BVTV9Pn8I334BGfoQTQgghhEgLtBot1fNWT7CTkKqq1M5f2+KY7Uu3t2hch9IdLI6ZEuoVrIdOozN7XqfR0aBQg9RLSAghhBDCRuTOnBBCJEO1vNVw1jonOq5ugbqpkI15jYo0SvRDbePCjVMxIyGEEEIIIYTIGEbVGmV2haYGDW5ObvSq2MvieKVzlaZItiIJjsnqmpWWJVtalaetDa0xNMFVtgajgferv5+KGQkhhBBC2IYUV4UQIhmyZ8pO70q9zT6FrFW0NCvWjOI5iqdyZrG9X/39BNstGVUj79eQD7VCCCGEEEKItElVVQLvBbLj6g6uPrlq73Ri6Vy2M8PfGA6YPiNG0ypanHXOrO28lmyZslkVc1evXbjp3OI9p9Po2NFzR9ITtpFKuSsx5+05KCixHvbVaXQoKMx9ey4Vc1e0Y4ZCCCGEEEkjxVUhhEim6W9Nj2nhFF1kVf79p2TOkixtu9Se6QFQ1qssi9ssRqNo4nyo1SgalrRdQplcZeyYoRBCCCGEEEIkzdpzayk5qySVf6pM418bU/THotRfXJ/Ae4H2Tg0ARVGY0XQGm7tupmnRpni5e5HfIz9Dawzl1OBTNCnaxOqYBTwLMLHRxFjFWjB9Fh3xxgiq5Kliq/STZVC1QRx67xCdy3YmT+Y85Mmchy7lunDovUMMrDbQ3ukJIYQQQiSJoqqqau8k0orQ0FA8PT0JCQnBw8PD3ukIIRxIlCGKP87+wYJjCwh6GkTuzLnpU6kP3St0x80p/qeJ7eHMgzPMDpjNjqs7QIHGhRvzfo33pbBqJZkPrOew71l4uGlP06xZTV+2cOUK3L0LZcpA9uzJj6eqpngGA+TNC1pt4tcIIYSDctj5wIHJeyZEwpadXEaPtT1QUFD57xaXVtHionNhf9/96XJ15Pyj8xm4yXxxcuybY5nUaFIqZiRSmswH1pP3TAghBKTMfCDFVSvIhCyEEAJkPkgKh3vPbt2CceNg+XKIiABFgWbNYPx4qF49aTFnzYIvvoAnT/47VqYM/P47lC1rfTxVhZ9/hm+/hcuXTcfy5YMRI2DUKNCZ30dZCCEclcPNB2mAvGdCmPci6gV5vstDSERIvOe1ipb6heo7RItcW3Ob6MYL/Quz5zWKhrBPwnDVuaZiViIlyXxgPXnPhBBCQMrMB9IWWAghhBAZy40bpgLq0qWmwiqYCpl//w116sCOJNx8+/xzGDYsdmEV4OxZqFgRTp60PuaoUTBggGklbLTbt2HMGOjc2bSSVQghhBAiA9t4caPZwiqAQTWw89pOrj+9nopZpby159YmWFgFMKpGpu2flkoZCSGEEEJkLDZb8vDw4UO2b9/O6dOnefLkCS9fvkz0GkVRWLhwoa1SEEIIIYRI3MiR8OgR6PWxjxsMpiJrjx6mAqylK0OfPoWJE82fNxjgnXfg0iXLc9y/H374wfTr15uMqCqsWQOrV5uKrEIIIYQQGVTQ0yB0ig69qk9w3M3QmxTMWjCVskp5J+6dsGjc+UfnUzgTIYQQQoiMKdnF1efPn/Phhx+yePFioqKirL5eiqtCiPTgpf4ly04uY/7R+dwIuYF3Zm/6VOpD38p98XBxnNYzx+4eY+ahmWy/th0w7bk67I1hVMlTJUnxjKqRtefWMvfIXM48PEMW5yx0KdeFwdUGkydLHlumLoRt3L8P69eD0Rj/eaPRtL/p1q3QsqVlMT/9NG4B9HWXL5sKtgUKWBZz3jxTcff1AnA0rRbmzJHiqhBCCCEytFxuuTCoiXfzyOmWMxWyST35PfNbNC5PZvlMJoQQQgiREpJVXI2KiqJp06YcPHiQpGzdqihKcl5eCCEcQmhEKI2XNibgTgAaNBgx8iDsAaP9RjM7YDZ7eu9xiELjgqMLGLhpIFqNFr3RVLBZdmoZS04s4aeWP9G/an+r4hmMBrr+2ZXfz/6OVtFiUA3c4x6T9k5i1uFZ7Oy1k0q5K6XAdyJEMly+bL6wGk2rhXPnLC+unjpl2bjDhy0vrp4+bb6wCqbVsGfOWBZLCCFELIGBgWzZssXqrks7ktI2XgiRotqWasvgvwYTYYiI97xG0VDeqzwlc5RM5cxSVq9KvRj016CYz3XmjHlzTCplJIQQQgiRsSSruDp37lwOHDiAoihkzpyZ999/nyZNmuDj44OLi4utchRCCIc2cutIjt09BoARU9FGxfTASdDTIHqs7cH2ntvtlh+Y2kYN3DQQFTXWB/DoXw/cNJCaPjUp713e4pgzDs7gj7N/AMR6WtygGgiNCKXlipYEjQxCp7FZB3ohki9z5sTHGI2WjbMmJkBOK1ZMeHiAoiS8ItaaHIUQQnD37l369OnDtm3brLpOVVV5MFgIB5UtUzY+qfsJ4/zHxTmnoKCqKlMaT0l3f4d1Gh3Dagzj+4Pfmx3TrlS7dLdiVwghhBDCUSTrjvfKlSsB8PT05MCBA5Qsmb6eBBRCiMQ8Cn/Eryd/NduKSm/Us+PaDs4/Ok+pnKVSObv/zAqYFWvF6uu0Gi2zA2Yzr+U8i+IZVSMzDs2IKSK/zqAauP3sNhsvbKRd6XZJzlsImytfHgoVgqAg82MUBdq0sTzmqFGwZUvCY1xcoF49y2N26gR79pg/r9XCu+9aHk8IITK458+f07BhQy5dupSkrktCCMf1eb3PAZi4dyKRhsiY41lds/Jz659pVqyZvVKL49qTayw4toBjd4/honOhVYlWvFvuXdyd3a2ONb3pdMIiwph/fH6ccy2Lt2R1x9W2SFkIIYQQQsRDk5yLz507h6IoDBo0SAqrQogM6eido4m2YgLYd2NfKmRj3u6g3QnmqTfq2Xltp8Xxbofe5lborQTHOGmc+OfGPxbHFCJVaDQwYYL584oC/ftD3ryWx2zSBAoWTHjMqFGm17ZUjx6QL59p39XXabWmVavvv295PCGEyOC+//57Ll68CICPjw9z587l8uXLvHz5EqPRmOiXwZD4no6WmDLFtIJu5MiRNoknhICQiBC2XN5CpCESBdMKVY2i4cnLJ/hd8cOoJrIlRCpZcHQBxWYW49t93+J3xY+NFzbSf2N/is8szrmH56yO9zzyOctOL4v33NbLW7kecj25KQshhBBCCDOSVVyNjDQ9EVipUiVb5CKEEGmOpe2l7N2GypLX1yiWTwlp5fsWIl49esD334OTk6ng6eRkKlgC9OoFP/5ofcxjx8DHJ/5z3brB5MnWxcuSBfz9oUgR0+91OlOeAF5esGOH+dcTQggRx9q1awHInTs3AQEBDBw4kCJFiuDs7JxqOQQEBPDTTz9RoUKFVHtNITKCHmt7EHA7APhve5bogur8o/OZtn+a3XKL5h/kz4BNAzCqxpiuR9G5Pgh7QJNfm/BSn/j+z68qNasU4VHh8Z7Tq3rKz7V8yxchhBBCCGGdZLUF9vHx4fLly0RERNgqHyGESFPeyPcGrlpXXhrMfxBWUGhQqEHqJRWPpkWbcvXJVbOrV3UaHU2LNrU4Xr4s+SiarShXn1w12xo4yhiFb2HfJOWb0ej1egICAjh9+jRPnjzh5UvLbqx88cUXKZxZOjZypKnouWwZXLsGOXKY2uyWKJG0eNmzw82bsH49fPcdhIZCsWIwdSoULpy0mEWLwrlz4OdnKqYajVC7tqllcXShVQghhEWuXLmCoigMGTIEb2/vVH/958+f061bNxYsWMDXX3+d6q8vRHp14dEFNl3clOCYqfunMqrmKJy09vv56dt936JVtPFuJxO9pcofZ/6gR8UeFsW79uQat5/dTnBMWFQYmy9tpkXxFknKWQghhBBCmJes4upbb73F5cuXOXLkCD16WPYDoBBCpCeerp68V+U95hyZE2+7Ka2i5e3ib1MkWxE7ZPef96u/z9wjcxMeU8PyFqOKovBh7Q8Z/NfgeM9rFS2FsxV2qP2NHJHRaOTbb7/l+++/59GjR1ZfL8XVZMqVy9Su15batLFuv9bEaDTQvLnpSwghRJIZjaaf0+y1nc3777/P22+/TePGjRMtrkZERMR6gDk0NDSl0xMizfK74odG0STY+vdR+CMC7wVSPV/1VMzsP0bVyN9X/o63sBpNq2jZcnmLxcXVyf9Y1hXlm3++keKqEEIIIUQKSFZb4OHDh+Pq6sqSJUu4d++erXISQog05dsm38as0NQqptai0S12K3hXYFHbRXbLLVrJnCVZ3n45Oo0uJkcw5avT6FjRfgUlcli3Ym9g1YEMqjYIMK18BdMqXQUFL3cv/ur6l1WthjMaVVXp2LEjn376KY8ePUJVVau+hBBCCGG5gv/ujf3s2bNUf+2VK1dy7NgxJlvYIn7y5Ml4enrGfOXPnz+FMxQi7YoyRMXss5qQSENkKmQTP1VVEyysgqkAa02OL6JeWDTOnt+3EEIIIUR6lqyVq8WLF2fevHn07duXpk2bsmbNGooWLWqr3IQQIk3I5JSJrd22svHiRhYcXUBQSBC5M+emT6U+dCzTERedi71TBKBT2U5UzVOVuUfmsv3qdgCaFGnCoGqDKJrd+v93K4rCnBZz6FK2C/OOzOPUg1N4unjSuVxnelXshaerp62/hXRl6dKlMfu/abVaOnToQJMmTfDx8cHFxTH+mxFCCCHSi9atW3P27Fn27dtHnz59Uu11b968yYgRI9i2bRuurq4WXTN27FhGjx4d8/vQ0FApsAphRvV81RMtXLpoXSjrVTaVMopLq9FSwbsCp++fxkj8K2wVRaF6XstX1vas2JNlp5YlOq5tqbYWxxRCCCGEEJZTVAuWvyxdujTB81u2bGHVqlU4OTnRsmVLatWqRc6cOdFoEl+x1LNnT8uztbPQ0FA8PT0JCQnBw8PD3ukIIYSwE1vMB76+vvj7++Pq6srWrVupV6+ejbN0LDKHCiGEAPvNB3fv3qVcuXKEh4dz/PhxSpUqlSqvu27dOtq1a4dW+1/nEIPBgKIoaDQaIiIiYp2Lj8yhQpinqipl5pThUvCleIusWkVLn8p9WNBqgR2y+8+i44vou6FvvOcUFJy0TtwadYtc7rksjuk20Y0XevMrWDVoMIxLuPAs0haZD6wn75kQQghImfnAopWrvXv3RlESbrOiKApRUVGsW7eOdevWWfTiiqKkqeKqEEIIYSsnT55EURTee++9dF9YdVjXrsGYMaZ/Z88On34KjvZnoaqwaxfs2AEGA9SpAy1aQCI34oUQQsSWJ08eVq5cSfv27WnSpAnLly9Plfm3UaNGnDp1KtaxPn36UKpUKcaMGZNoYVUIkTBFUfij4x/UW1SP0IjQWAVWjaKhrFdZpjWZluT4BqOBi8EX0Rv1FMtejExOmZIUp1elXuy4toPlp5bH2iNWp9Ghqior2q+wqrAKsK3HNt5c9KbZ80vaLUlSrmAqWl99cpXnkc8pmLUgWV2zJjmWEEIIIUR6ZHFbYEv3d5N94IQQQojEhYWFAVC7dm07Z5JBdekCq1bFPvb331CqFBw/Dha2bkxRQUHQqhWcPg06HSgKfPMNFCgAGzZAxYr2zlAIIRzOhAkTEjzfuHFj1q9fT8OGDalUqZJVXZe++OILq/PJkiUL5cqVi3XM3d2dHDlyxDkuhEiacl7lODn4JDMOzmDpiaU8ffmUAp4FGFRtEIOrDcbd2d3qmKqqMjtgNt/s+4ZbobcAyOKchQFVBzCh4QTcnNysiqdRNMxqMYsHYQ/YcXVHzHEXrQuja46mfen2VudYp0AdTg0+RbuV7bj85HLM8XxZ8rGs3TIaFG5gdUyANefWMM5/HKcfnAbASeNEt/LdmNx4Mrkz505STCGEEEKI9MaitsBLliT9abfE9OrVK8Vi25q0khBCmBMWGcbC4wuZf3Q+t0JvkdMtJ30r92VQtUFkz5Td3unF2HdjHz8c+oGd13YC4FvYlxFvjKBOgTp2zixtscV8ULRoUYKCgvj111/p2rWrjTN0PA41hw4bBrNmmT9fvjycPJl6+cQnLAzKlYNbt0Cvj31OqwUPD1PRNW9e++QnhBBJlNLzgUajSbTrEpgKJ5aMe5XBYJv2mg0aNKBSpUrMmDHDovEONYcKkUGM2DqCHw/9GOe4RtFQM19NdvTagavO8ofxnkc+581f3uT0g9OxVtcqKKiofFHvC8Y3HG+T3JPjpyM/MeivQTF5RdNpdOTNkpfD7x3GO7O3HTPM2GQ+sJ68Z0IIISBl5gOLiqvCRCZkIUR8nrx4QoMlDTh139TyLfpDqEbR4OPhwz99/iG/Z347Zmjy46EfGbF1BDqNDr3RVKyJ/vXM5jMZWmOonTNMO2wxH/Tp04elS5fy0UcfMWXKFBtn6HgcZg41GsHFJW7B8nUnTkCFCqmTU3x++gkGDza1BY6PVgv/+x98/XXq5iWEEMmUGsXVlKAois2Kq9ZymDlUiAzi6J2jVFtQzex5BYUfm/9o1eenSXsn8fmuz2PaAcfnwtALlMhRwqpcbSk4PJi80/MSaYiM97xO0dG/an/mvD0nlTMT0WQ+sJ68Z0IIIcCOe64KIYQwb/iW4Zx5cCbWk70ARtXInWd36L6mO7v77LZTdibH7h5jxNYRADGF1Vd/PWzLMOrkr0PlPJXtkl9GNGzYMJYtW8bixYv59NNPyZIli71TyhjWrEm8sAqm9rvLl6d8PuasXJnweYMBVqyQ4qoQQrxm165d9k5BCJHGzT86P9YDqfGZd2SeVcXVOQFzEiysahUtC48t5Jsm31iVqy0tP7WcKEOU2fN6Vc/iwMV899Z3Sd57VgghhBAivUhWcfXGjRsAeHl54WrF3mQRERHcv38fgAIFCiQnBSGEsKsHYQ9YeWZlrNZOr9Ib9ey5sYfTD05Tzst++2rNPDwzwRsEOo2OWQGzWNh6YSpnlnFVqVKFr7/+mrFjx9K2bVtWr15NtmzZ7J1W+vfwoWXjnj5N0TQSFRJiftVqtNDQ1MlFCCHSkPr169s7BSFEGncx+GKChVUVlStPrlgcT2/Uc/vZ7QTHGFVjrH1T7eHy48voNDqijOYLrC/0L3gQ9oCCWQumYmZCCCGEEI4nWcXVQoUKodFoWLNmDa1bt7b4On9/f5o3b45Go0FvyeoRIYRwUMfuHkvwg3e0g7cO2rW4uvf63gTz1Bv17Anak4oZZRx79ph/X2vVqkXXrl1ZsWIFJUqUoGfPntSqVYucOXNa1NawXr16tkw1Y6hVy7JxFSumbB6JKVMGTp0yv8pWo4FSpVI3JyGEEEKIDCBbpmxoFE2CK009XCxvJ6dVtGTSZeKF/oX5MRotni6eVuVpa1lds8bpxhQfa753IYQQQoj0KtltgZOzZats9yqESOu0itaicTqNfbuwW/L6Oq10ik8JDRo0QFGUBMcoikJwcDAzZsxgxowZFsVVFEUeUEqKSpXA2xv+7aARL0WBL75ItZTiNXBgwm2JjUYYMiT18hFCiDQu+mGncuXKkT17douve/r0KSdPngTkoSYhMoou5bqw9vxas+e1ipbu5btbHE9RFLqU68KvJ381+8Cr3qinS7kuVudqS53KduKrPV+ZPa9VtDQs3JBsmaTbjhBCCCFE4stihBBCmPWGzxtk0iW834yCQsNCDVMpo/i1KN4iwUKwVtHSoliLVMwoY1FVNdEvS8e9fo1Igt9/NxVQzfnyS7Biu4MU8eabMGhQ/Oc0GmjZEjp3Tt2chBAiDWvQoAENGzbkn3/+seq6Q4cO0aBBA3x9fVMoMyGEo2lXqh3lvcrH+4CqVtGS2Tkzw98YblXMj+t8jJPGCY0S9zacVtFSy6cWjYs0TnLOtlDOqxwdy3SMN0cF08/O4+qPS+20hBBCCCEckl2WKT179gwANzc3e7y8EELYjIeLB4OrDWbGoRnxto3SKlralW5n9z1phlQfwqzDszCqxjitnhQUNIqGIdVlFVxKGDdObkA4nHr1YO9e6N4dgoL+O54tG0yebFo1am+KAnPmQNmyMG0aXL9uOu7lBcOGwZgxoLVs5bwQQojkk4eahMg4nLRObO+5nfar2rPv5r6YwqKKSt4seVnfZb3Vn+9K5SzF9p7b6fB7B+4+v4uTxgmjasSgGmhcpDErO6yMt6iZ2pa0XYKTxokVp1egUTRoFS1RxiiyumZlSdslvFngTXunKIQQQgjhEOxSXN2+fTsAefLkscfLCyGETU1uPJlLjy+x8eJGtIoWg2qI+Xf1fNX5udXP9k6RYtmLsbrTajr+0RGD0YBBNQCm4q9Wo2V1x9UUzV7UzlmmT1JcdVB16sC1a3Drlmlv0wIFTIVMR6IoMHSoqf3v9eumVsAFC4JOWngLIURqiS6qJtbiXwiRvjx58YSboTcB08OoKioKCo/CH3Hn2R0q56lsdcza+WtzY9QN/rr4F8fvHcdF60LLEi0p713e1uknWSanTCx/ZznjG45n7bm1PI98TulcpWlXqh0uOhd7pyeEEEII4TAsvju3e/dudu/eHe+5lStXEhgYmOD1qqoSFhbGsWPH2LVrF4qiULt2bauSFUIIR+SsdWZdl3Vsu7KNhccXEvQ0iNyZc9OrYi/alGpj9/1Wo7Uu2ZrLwy4z/+h8dgXtAsC3sC8Dqg7Ax8PHztkJYSc+PqYvR6bRQOHC9s5CCCEypKdPnwLSdUmIjCQsMgzfpb7cf34fACP/dSh6qX9Ju1XtODbwGOW8ylkdW6fR0aZUG9qUamOzfFNCsezF+KjOR/ZOQwghhBDCYVl8x9/f358JEybEOa6qKqtWrbLqRVVVxcnJieHDrdujQgghHJVG0dC0WFOaFmtq71QSlN8zP1/5fmXvNIQQQggh0oQ1a9YAUKBAATtnIoRILStOreDOszvxnlP//ef7g9+zsPXCVM5MCCGEEEI4CquWU5nbZ8ba/WeqVKnCpEmTqFKlilXXCSGEEOmFRqNBo9GwZs0aWrdubfF1fn5+tGjRAkVR0Ov1KZihEEIIkTatX7+e9evXx3vuxx9/ZN26dQleH911KTAwkCtXrqAoCvXq1UuBTIUQjmj9hfUxrYDjozfqWXNujRRXhRBCCCEyMIuLq71796ZBgwYxv1dVFV9fXxRF4auvvqJOnToJXq/RaMicOTOFCxcma9asSc1XCCGESDesfTgpudcJIYQQGUFgYCCLFy+Os0+qqqrs2rXLqliqquLu7s7o0aNtmaIQwoGFR4WbLaxGi9BHpFI2QgghhBDCEVlcXC1YsCAFCxaM91y5cuWoX7++zZISQoiUpKoqK0+vZObhmQTeC8RZ60ybUm0YVXMUlXJXSlLM0IhQ5gbMZf7R+dx5foccmXLQp1Ifhr0xDC93ryTF3HZlG6P9RnPm4RlUVFx1rnQs3ZF5Lefh5iz7fokMRFVh3Tr44QcICACtFlq0gNGjoUaNpMV89Ajeew82b4aoKNO+ptWqwezZpn8LIYRI8+J7GMmaB5Q8PT1p1KgR48aNo1ixYrZMTQjhwCrnrszeG3vRG+PvEqNRNJT3Lp/KWQkhhBBCCEeiqMlY/rJ7927AVFzNkSOHzZJyVKGhoXh6ehISEoKHh4e90xFCJIFRNdJ3fV+WnFiCRtFgVI0A6DSmZ03+6PgHbUu1tSrmo/BH1F1Ul4vBF2PiAWgVLV7uXuzru4/C2QpbFXNOwBze3/x+vOdyZMpB0MggMjtntiqmsB1bzAcajQZFUVi7dq1VbYHXrl3LO++8Q6ZMmQgLC0vSa9tDkt8zVYURI2DmTFNR1WAwHdfpTL9esgR69LAumVu3oEQJePEi7jlFMRVyrfgzEUIIYbnU+EwVEhLC06dPY36vqipFihRBURR++uknmjRpkuD10V2XsmXLliL5WUs+hwqRui4GX6TUrFIJrl79td2vdK/QPRWzEkLmg6SQ90wIIQSkzHxg1Z6rr5PVqkKItGbpiaUsObEEIFYhVG/Uo6DQZXUXbo66SS73XBbHHLp5KJeCL8WKB2BQDTwMe0i3Nd3Y32+/xfFCX4YydPNQs+eDXwTTbmU7tvXcZnFMkX4cPHgQAC+vpK2ITnPWrTMVVuG/wipA9H6zffpAvXpgprtGvJo0ib+wCqZibseOpvMaTZJSFkIIYV+enp54enrGOa6qKl5eXmY7Mgkh0r7QiFBCXoaQyz0XrjrXJMUokaME05tOZ5TfKLSKFoNq+hk0eh/WLuW60LV8V1umLYQQQggh0phkFVeFECKtmXFwBho0GDHGOaeiEmWMYlHgIj6u87FF8e49v8fqs6tjPnC/Tq/qOXDrACfunaBi7ooWxRy7c2yie/zsvLaTl/qXSb5hIFLXyZMnCQwMjPfczp07Y62uiY+qqoSFhXHs2DGWLVuGoihUr17d9ok6oh9+iL1iNT7z58PEiZbFu3EDzp9PeExkpKk98LBhlucphBDCoV27dg3IQA8nCZHBHL1zlC93f8nmS5sxqkZcda70rNCTcQ3GkTdLXqvjjaw5kpI5SvLt/m/xD/IHoGTOkox8YyT9q/ZHo8hDeEIIIYQQGVmyiqs3btxI0nUajYYsWbLg4eGBoijJSUEIISxmMBo4cf9EgmNUVSXgToDFMQPvBZotrL4q4E6AxcXVAzcPJDrGiJET907whs8bFsUU9rV27VomTJgQ57iqqsyMXpVpIVVVURSFQYMG2So9xxYQkHBh1WCAQ4csj7d1q2Xj/v5biqtCCJGOyGpVIdKvXdd20Wx5MwxGQ0w3oZf6l/xy/Bc2XtzIofcOkd8zv9VxmxdvTvPizYk0RGIwGsjklMnWqQshhBBCiDQqWcXVQoUKJas4qtPpKFu2LA0bNmTAgAGULFkyOekIIUSCFEWJtc9qfDSKBieNk8Uxo/dqTYw1MbWK1qJx8uE+bTG3xbm1W597e3szceJEfH19bZGW49Mm8vdBUcDZ2fJ4Li6WjbMmphBCCCGEsAuD0UD3td3RG/VxPufpVT0Pwx8y2m80f3T6I8mv4ax1Bss+ogkhhBBCiAwi2W2Brb0p/KqoqChOnDjBiRMn+PHHHxkzZgxff/11clMSQoh4aRQNbxV5i21Xt5ldbWpQDTQr1szimDV9auLu5E5YVFiCr9uoSCOLY3Yq24kjd48kOMZF60K5XOUsjinsq23bthQqVCjWsT59+qAoCkOHDqVKlSoJXq/RaMicOTOFCxemfPnyaBMrOKYnb78Nq1f/t8dqfJo3tzzeO++Y9mlN7OeX996zPKYQQgiHt2fPniRdF911KXv27OTPb/3KNyFEytp6eSt3nt0xe15v1LP2/FruP7+Pd2bvVMxMCCGEEEKkZ8kqrvbq1QuAW7dusWPHDgC0Wi1ly5alSJEiuLu7ExYWxtWrVzlz5gwGgwFFUWjUqBHe3t4EBwdz9OhRHj58iMFgYPLkyej1eqZMmZL870wIIeLxUZ2P2Hol/ragWkWLl7sXHct0tDheZufMDK0xlG/3fRvvPqlaRUvncp3x8fCxOOYHtT7g812fE2GIMDumT6U+aDSyz09aUbFiRSpWjN0Wuk+fPgA0atSI1q1b2yOttGH0aPj99/jPabXg6Qk9e1oeL3NmaNLE1PbXnFy5rCvYCiGEcHgNGjRI9pY0WbNmpUGDBgwZMoRGjSx/cE4IkXLOPjyLVtEmuFWLQTVw6fElKa4KIYQQQgibSdad+UWLFtGnTx8CAwNxdnbms88+486dOwQGBrJmzRp+/fVX1qxZQ2BgIHfu3OHTTz/FycmJwMBABgwYwObNm7l37x7Lly8nW7ZsqKrKtGnTOHfunK2+PyGEiMW3sC9z356LRtHEtN9V/v0np1tOtvXYZnW73a8afhVTkI1uExwd+80Cb/JTy5+siqfRaNjde7fZVsJ1C9Rlbsu5VsUUjmfRokX88ssvia5azfCqV4clS0Cn+69FsKKYvjw8wM/PVGC1xl9/QYkS8Z9zd7duD1chhBBphqqqyfp68uQJ69at46233qJ79+5ERUXZ+1sSIsPL7Jw5wW1fXh0nhBBCCCGErShqMvr63rlzh4oVK/LkyRM2btxIcwtWefz111+0bt2anDlzEhgYSJ48eQD4559/qF+/PgDDhw/n+++/T2paKSY0NBRPT09CQkLw8PCwdzpCiGS48vgK84/O58jdI2TSZaJ1ydZ0Ld81yR+6VVXlnxv/sPD4Qq4/vU7uzLnpWbEnTYs1RaMk7TmW0Jeh/G/H/1h7bi0v9S/J75mf8Q3G0650uyTFE7Yj84H1kv2e3bgB8+fDwYOm/VCbNzetWLW2sBrNaIRffoFp0+DePciSBXr0gC++AFfXpMUUQgiRKHvNoePHjwcgMDCQ9evXA5AjRw7q1KkTp+vSvn37CA4ORlEUWrduTbly5QgODubw4cMcO3YMAEVR6N69O0uWLEnx3OXnDiHMux16mwIzCiRYYC2UtRBXhl9J8ucyIRyFzAfWk/dMCCEEpMx8kKzi6tixY/nmm2/o1KkTK1eutPi6Tp068eeffzJmzBgmTZoUc/ztt99my5YtVKpUKeZDqyORCVkIIQTIfJAU8p4JIYQA+84Hf/zxBz179sTV1ZXvvvuOnj17otPF3SlHr9ezZMkSPvzwQyIiIli6dCkdOnQA4MCBA3Tt2pXr16+jKAr79u2jZs2aKZq3zKFCJGzAxgEsPL7QbIF1cZvF9KrUK5WzEsL2ZD6wnrxnQgghIGXmg2Q9trdx40YUReGtt96y6rqmTZuiqiobNmyIdbxx48YA3LhxIzlpCSGEEEIIIYQQMS5evEifPn1QVZUdO3bQt2/feAurADqdjn79+rFt2zYMBgN9+/bl0qVLANSqVYu//vor5trFixen1rcghDBjVotZvFvuXcC0PYuTxgmNokGn0TG1ydR0X1i98+wO3/zzDUM3D2XC7glceXzF3ikJIYQQQqR78X+atFB0ETRzZuvaaGbJkgWAmzdvxjqeL18+AJ49e5actIQQDkJVVRRFsXcaIh7RTQts+edjNBrRaKTV1uu00fuE2piiKOj1+hSJLYQQQqQ3M2fOJDw8nH79+lm833m1atXo3r07ixYtYubMmfz4448AlClThrZt27J69Wr27duXkmkLISzgrHVmWftlfFL3E1aeXklweDCFsxWmR4UeeGf2tnd6KUZVVSbsnsCEPRNQUNAoGoyqkXH+4xhcbTAzm89Eq0mZzyJCCCGEEBldsu6CR99Ev3DhglXXnT9/HjB/U1/aNAiRdgU9DWL4luFknZIVzQQN+b/Pz8Q9EwmNCLV3agLYdHETDZc0xPlrZ5y/dsZ3iS9/XfwryfFCX4bSflV7nL9yRvuVFmW8QvEfi7PhwobEL84gVFVNsS8hhBBCWObvv/9GURTq1q1r1XX169cHwM/PL9bxevXqAXD79m3bJCiESLYyucowoeEEZr89mw9rf5iuC6sAsw7P4svdX2JUjRhUA1HGKAyqAYB5R+YxdsdYO2cohBBCCJF+Jau4WqxYMVRV5ZdffuHFixcWXRMeHs4vv/yCoigUK1Ys1rk7d+4AkCNHDoti3b59m+7du5MjRw4yZcpE+fLlOXLkSILX+Pv7U6VKFVxcXChWrJi0cRLChk7cO0GleZWYe2QuIREhANwKvcUX/l9Qa2Etnrx4YucMM7bx/uNp9Vsr9l7fi96oR2/Us+f6Hlr+1pIJuydYHe9x+GMKzCjA2vNriTJGxRy//OQybVa2YfqB6bZMP82qV68e9evXN/tVqVKlWOOzZMlCpUqVqFOnDpUqVYr1wJGiKFSuXJn69evH3NQVyRAZCUOHQr160LEj3LuX/JgPHsDYsfDeezB3Lhjj3/sr3dHrwc8PFi82/VtWVQshHMytW7cAcHZ2tuq66PGvF1Fz584NQFhYmA2yE0II60QZopiwx/xnOBWVHw/9KJ/BhRBCCCFSSLKKq+3btwdM7YHbtGnDo0ePEhwfHBxMmzZtYtoJd+jQIdb56MJowYIFE33tJ0+eUKdOHZycnNiyZQtnz57lu+++I1u2bGavuXbtGm+//TYNGzYkMDCQkSNH8t5778V5ClkIYT1VVem0uhPPI5+jN8a+qW5UjVx4dIEP/v7ATtmJ/Tf38+XuLwFinmZ+9dfj/Mdx4OYBq2K2W9Uupogenw///pCnL59anWt64+/vz65du+L9+vHHHwkJMb2HHTp04NChQ4SEhHDs2DH27t3LsWPHePr0KYcOHaJjx46oqkpISAgzZ85k165ddv7O0rh+/cDFBWbPhr17YfVqyJMHKlUCgyHRy+MwGqF5c/D2hilTYOFCGDIEXF1hzhybp+9QVq4EHx9o1gz69DH928cHfvvN3pkJIUQMV1dXAE6ePGnVdSdOnADAxcUl1vHo1vxZs2ZNfnJCCGGlA7cO8Cg84XtwEYYItlzekkoZCSGEEEJkLMkqro4cOZICBQoAsGPHDkqUKMGwYcNYs2YNJ06c4NKlS5w4cYI1a9YwbNgwihcvzs6dOwEoUKAAI0aMiIkVGRnJli1bUBSFN998M9HX/uabb8ifPz+LFi2iRo0aFC5cmLfeeouiRYuavWbevHkULlyY7777jtKlSzN06FA6dOjA999/n5y3QQgB+Af5czH4YqzC3asMqoHlp5bLk7N2MuvwLHQa89ts6zQ6ZgfMtjheeGQ4e2/sTXCMisrY7dKKypzHjx/TsmVLgoKC+P777/n999+pXr16vGOrV6/OqlWr+OGHH7h69SqtWrXiyZOk/12aO3cuFSpUwMPDAw8PD2rVqsWWLeZvvCxevBhFUWJ9Rd+kTpOGDYNffon/3IkTULGi9TEbNYKtW+Mej4qC99+HJUusj5kW/P47vPsu3L8f+/j9+9C1K6xaZZ+8hBDiNaVLl0ZVVRYuXEhwcLBF1zx8+JCFCxeiKAqlS5eOdS76gWFLuy4JIYQtPY98btNxQgghhBDCOskqrrq5ubFlyxa8vb1jVtPMmTOHjh07UqVKFUqVKkWVKlXo2LEjc+bMISQkBFVVyZMnD1u3biVTpkwxsY4fP07t2rVp0aIFnTt3TvS1N2zYQLVq1ejYsSNeXl5UrlyZBQsWJHjNgQMHaNy4caxjTZs25cCB+FdrRUREEBoaGutLCBG/o3ePolW0CY6JNERy9uHZVMpIvOrQ7UNxVhS/Sm/Uc/DWQYvjHb93HJXE9/w8dPuQxTEzmtmzZ3Pz5k18fX1jPWyUkGHDhuHr68uNGzeYPdvyYvjrfHx8mDJlCkePHuXIkSP4+vrSpk0bzpw5Y/YaDw8P7t69G/N1/fr1JL++3SX23p05A+fOWR7vzBnw9094zKhRlsdLKwyGxL+v0aOTthJYCCFsrEuXLgA8evSIRo0aceHChQTHnz9/nsaNG8d0Z+ratWus84cOHUJRlAQf7hVCiJRSMkdJi8aVzlk68UFCCCGEEMJqySqugukJ4JMnT9KjRw90Oh2qqpr90mq19OzZkxMnTlCyZOwfBN944w02btzIxo0bKVGiRKKve/XqVebOnUvx4sXx8/Nj8ODBDB8+nCUJrAy5d+8e3t7esY55e3sTGhoa756xkydPxtPTM+Yrf/78Fr4rQmQ8LloXjGriewu66FwSHSNsz0Wb+PtuzZ+Nu5O7ReOctdbta5aRrFmzBkVRYlrsW6pDhw6oqsqff/6Z5Ndu1aoVLVq0oHjx4pQoUYKJEyeSOXNmDh40X2BXFIXcuXPHfL0+n77OYR9QWrwY1MQfDGDwYMtjfvll4mOePIHAQMtjpgW7d8OdOwmPuXMH9uxJnXyEECIBgwYNokKFCqiqyqlTp6hQoQKtWrVi+vTprF+/nm3btrF+/XqmT59Oq1atqFixIqdPnwagQoUKDBw4MCbW8+fP+fvvvwGoX7++Xb4fIUTGVjR7URoWamj2AWetoqV49uK8WSDxznBCCCGEEMJ65ntEWiFnzpwsWbKEqVOn8tdffxEQEMCdO3cICwvD3d2dvHnzUr16dVq0aJHozVhLGY1GqlWrxqRJkwCoXLkyp0+fZt68efTq1csmrzF27FhGjx4d8/vQ0FApsAphRvPizRm+dXiCY7zcvaiUu1LqJCRiaVuqLRf3mW/brFW0tCvVzuJ4Fbwr4Kpz5aX+ZYLjulfoblWeGUlQUBBgmkOtEd1+MPr65DIYDPzxxx+EhYVRq1Yts+OeP39OwYIFMRqNVKlShUmTJlG2bFmz4ydPnsz48eNtkqNNWbrX3r17lse0dOzFi6Y9XdOL11sBm2PNeymEEClEp9Ph5+dH48aNOXPmDFFRUWzevJnNmzfHO17990GccuXKsWXLFrTa/woYly5donfv3sB/K2KFEI5Bb9Tz9OVTsrtmR6NJ9noChzav5TxqLaxFaERorC5FWkWLs9aZpe2WoiiKHTMUQgghhEi/bFJcjebl5UWfPn3o06ePLcPGK0+ePJQpUybWsdKlSye4kid37tzcf+1G4P379/Hw8IjVojiai4sLLi6yyk4ISxTLXox2pdqx4cIGswW8j2t/nOC+nyLlDKo2iBkHZxBhiIizwlijaHDRuTCw6kAzV8el0WgYUGUAPx7+0ewYNyc3hlQbkuSc0zu93nQD5Nq1a1ZdFz0++vqkOnXqFLVq1eLly5dkzpyZtWvXxplXo5UsWZJffvmFChUqEBISwrRp06hduzZnzpzBx8cn3msc9gGlatUsG2fm+4qXpd+Xmfc3zcqXz7bjhBAihXl7e3PkyBEmTZrE3LlzY1r+xidHjhy8//77jB07Ns5nwsqVKzNz5syUTlcIYYUtl7YwfMtwLj+5DICCQk2fmvza7leKZk+f7btL5CjBkf5HmLB7AstPLSfKGIVG0dC2VFvG1R9Hee/y9k5RCCGEECLdUlTVkt54jqdr167cvHmTvXv3xhwbNWoUhw4dYv/+/fFeM2bMGDZv3sypU6dixXn8+DFbt25N9DVDQ0Px9PQkJCQEDw+P5H8TQqQzoRGhtPqtFXuu70Gn0aE36mP+PbTGUH5s9qM8OWtH/kH+tPqtFWGRYbGOuzu7s/HdjTQo1MDqmE1/bcrfV/+Oc9xF68Lh/oep4F0hqek6NFvMBxUqVOD06dOUKlWKkydPotMl/uCBXq+nQoUKnD9/nnLlynHS0lWY8YiMjOTGjRuEhISwevVqfv75Z3bv3m22wPqqqKgoSpcuzbvvvstXX31l0es51Byq1YIxkTbmV69C4cKWxbtyBYoVS3hMrlzw4IFl8dIKoxGKFIEbN+JvtawoUKCA6b1M5ytHhBCWc5T5ICoqin/++cds16U6derg7OwY2xs4ynsmhKNadHwRfTf0jfecTqMjcGAgZb3Md1xJD8KjwnkU/ohsrtnI4pLF3umIFJIe5oPZs2czdepU7t27R8WKFZk5cyY1atQwO/7p06d8+umnrFmzhsePH1OwYEFmzJhBixYtLHq99PCeCSGESL6UmA/S7BKyUaNGUbt2bSZNmkSnTp04fPgw8+fPZ/78+TFjxo4dy+3bt1m6dClg2mdn1qxZfPzxx/Tt25edO3fy+++/89dff9nr2xAiXfFw8WBXr11sv7qdFadWEBweTOFshelXuR8Vc1e0d3oZXoNCDbgx8gZLTixhz3XTHoj1C9anV6VeZHXNmqSYfj382HZlG5/u/JQbITdw1bnSuWxnxjccj6vO1YbZpz9t2rTh9OnTXLhwgZ49e7Jo0aIEuyVERkbSt29fzp8/j6IotG3bNlmv7+zsTLF/C4JVq1YlICCAH374gZ9++inRa52cnKhcuTKXL19OVg5287//wb/bCsSrenXLC6sARYvC229DQj9PzJljeby0QqOBmTOhTRtTIfXVAmv0gzQzZ0phVQjhkJycnGjYsCENGza0dypCiGTQG/UM2DQgwfOtfmvF1RFXUzGr1Ofm5EYBzwL2TkOIBK1atYrRo0czb9483njjDWbMmEHTpk25cOECXl5eccZHRkbSpEkTvLy8WL16Nfny5eP69etkzZo19ZMXQgghXpNmV64CbNq0ibFjx3Lp0iUKFy7M6NGj6d+/f8z53r17ExQUhL+/f8wxf39/Ro0axdmzZ/Hx8eHzzz+P2S8nMfK0kxBCCLDNfPD06VNKlSrFw4cPAShQoABDhgzB19eXYsWK4ebmRnh4OJcvX2bnzp3MnTuX69evo6oq3t7enD9/Hk9PT5t9T76+vhQoUIDFixcnOtZgMFC2bFlatGjB9OnTLYrvcHPoxx/DtGlxV1zWqwe7dyctZteusHJl7JhubjB/PnTrlvRcHd2mTTBypGkFb7SiRWHGDGjZ0l5ZCSEclMPNB2mAvGdCmDflnymM3TE20XEXh16keI7iqZCRECknrc8Hb7zxBtWrV2fWrFkAGI1G8ufPz7Bhw/jf//4XZ/y8efOYOnUq58+fx8nJKUmvmdbfMyGEELaREvOBTYqrISEhLFq0iC1btnD69GmePHlCRERE4i+uKMneMy41yYQshBACbDcfBAQE0LRpU54+fWpRy2xVVcmaNSt///031SzdOzQeY8eOpXnz5hQoUIBnz56xYsUKvvnmG/z8/GjSpAk9e/YkX758TJ48GYAJEyZQs2ZNihUrxtOnT5k6dSrr1q3j6NGjFrURBgedQw0G+PZbOHTItG/q5MmQOXPyYoaHw9y5phbANWrAO+/YJldHp6pw8CDcvQt58kDNmv+tXhVCiFc45Hzg4OQ9E8K8lita8telxLuRzWkxh8HVB6dCRkKknLQ8H0RGRuLm5sbq1atjdWHq1asXT58+Zf369XGuadGiBdmzZ8fNzY3169eTK1cuunbtypgxY9BqtfG+TkRERKx70qGhoeTPnz9NvmdCCCFsxyHbAu/Zs4cuXbpw//59wHTjVwghhGOLMkQB4KRN2tOfaZXBaMCgGnDWOsYeatWrV+fYsWMMHDiQbdu2JTr+rbfeYt68eRQqVChZr/vgwQN69uzJ3bt38fT0pEKFCjGFVYAbN26geaWV65MnT+jfvz/37t0jW7ZsVK1alf3791tcWHVYWi2MTXylg1Xc3OCDD2wbMy1QFKhVy95ZCCGEVSIjI3n69CkvX760aHyBAtJyUwhHk8kpk0XjsjjLPqRC2NOjR48wGAx4e3vHOh7dlSk+V69eZefOnXTr1o3Nmzdz+fJlhgwZQlRUFOPGjYv3msmTJzN+/Hib5y+EEEK8LlkrV4OCgihfvjzh4eExRVUfHx98fHwS3DfuVbt27Urqy6e6tPyEmBBCqKrKH2f/YPqB6Ry6fQiAN/K9wQe1PqBDmQ4WrZxMq3YH7eabfd/gd8UPo2qkRI4SDK8xnIHVBqLTWP+cUUrMB6dOnWLNmjUcPnyYO3fu8Pz5czJnzky+fPmoUaMG7dq1o3z58jZ5LXuQOVQIIQTYfz64du0aP/zwA1u2bOHKlSsWPxxsz65L9n7PhHBk/9z4h7qL6iY4RqNoePHJC5x1jvGApRBJlZbngzt37pAvXz72799PrVceyvz444/ZvXs3hw4dinNNiRIlePnyJdeuXYtZqTp9+nSmTp3K3bt3430dWbkqhBAiPg63cvXbb78lLCwMRVFo1qwZ33//PSVLlrRJYkIIIWxr7I6xfLPvGzTKfysSA+4E0Gl1J/5X539MbjzZjtmlnEXHF9FvQz80igajagTgUvAlhm0Zxrar21jdaXWSCqy2Vr58+TRdPBVCCCEc3apVq+jXrx8vXrwApOuSEOnBmwXepIBHAW6E3jA7pn3p9lJYFcLOcubMiVarjel8GO3+/fvkzp073mvy5MmDk5NTrBbApUuX5t69e0RGRuLsHPfvtYuLi8ULfoQQQojkSNbd5G3btqEoClWqVGHTpk2xWggKIYRwHNErN4GYAuOrv56ybwotiregbsGEn/pOa26H3mbApgGoqBhUQ8xxFdPN1A0XNvDzsZ8ZVG2QvVIUQgghRCo4deoUPXr0wGAwoKoqrq6uVKtWzaquS0IIxxTQP4Cyc8vyKPxRnHM189Vk1Tur7JCVEOJVzs7OVK1alR07dsTsuWo0GtmxYwdDhw6N95o6deqwYsUKjEZjzD3nixcvkidPnngLq0IIIURqSlZx9fbt24Bp83EprAohhOOaEzAHnUaH3hh/OzudRsfsgNnprri68PjCRFel/HjoRymuZkSRkVCmDFy58t8xDw/YuxcqVEhazPBwWLECfvsNgoOhdGkYMAAaNDDtSZoUR47A6NFw7BioqinmN99Ao0ZJiyeEcCj7buxj3tF5nH5wGg8XDzqX7UyPCj3I4iJ7A9ra1KlT0ev1KIrCe++9x9SpU/H09LR3WkIIG/DK7MX9D+7z09GfmBMwh5CIEPJlyceEhhNoUrSJvdMTQvxr9OjR9OrVi2rVqlGjRg1mzJhBWFgYffr0AaBnz57ky5ePyZNNXbUGDx7MrFmzGDFiBMOGDePSpUtMmjSJ4cOH2/PbEEIIIYBkFlfd3NyIiIggT548tspHCCFECjhy94jZwiqA3qjnyJ0jqZhR6jhx/0SslbqvU1E59+gcBqMBrUZrdpxIZ+7dg/h+dgkNhYoV4ccfYdgw62LeumUqol65YiqkqiqcOQMrV0KfPvDzz2Dtg2gTJ8Jnn8U+dvQoNG4MAwfCvHnWxRNCOAxVVRmxdQQzD8+MefhJQWHv9b1M/mcy/r38KZq9qL3TTFd2796Noig0aNCA+fPn2zsdIYSNaTQaBlcfzODqg+2dihDCjM6dO/Pw4UO++OIL7t27R6VKldi6dSve3t4A3LhxI9binfz58+Pn58eoUaOoUKEC+fLlY8SIEYwZM8Ze34IQQggRI1nF1RIlSnDo0KE4/fKFEEI4lky6TDYZk9a46lzRKJpYLYFf56RxirUPra317dsXAEVRWLhwYZzjSfV6PGGFfPkSPj98uHXFVVWFtm3h+vX/fg+g//eBhkWLoGxZ+OADy2MeORK3sPqqn36Chg2hc2fLYwohHMbPx35m5uGZADEPP0W3rL/37B5vr3ibs++fTdH5KaN58OABYLqxK4QQQgj7GDp0qNk2wP7+/nGO1apVi4MHD6ZwVkIIIYT1klVc7dKlCwcPHmTTpk0MGTLEVjkJIYSwsfal23P+0XmzRUatouWdMu+kclYpr1WJVqw4tcLseZ1GR+uSrVGS2rLVAosXL46J/2ox9NXjSSXF1SQ4eRKM5lczx2jTBtavtyzmgQOmFaUJmTYNRowAnYU/ellSiP30UymuCpEGqarKt/u/RUGJKai+Sq/quRB8gb+v/E2zYs3skGH65OnpycOHD8mePbu9UxFCCCGEEEIIkcYl61HogQMHUq5cOfz8/Fi7dq2tchJCCGFjA6sOJJNTpnhXwGgUDW5ObgyoOsAOmaWs9qXbUzhrYXSauAUtBQWjauTD2h+meB7m9n1VVTXJXyKJLH0YzM/P8pg7diReNL13Dy5dsjxmYsVagGvXLI8nhHAYd57d4fLjy/EWVqPpNDp2XN2Rilmlf2XKlAHg5s2bds5ECCGEEEIIIURal6yVqy4uLmzYsIG3336bLl268OmnnzJ8+HCyZs1qo/SEEELYQj6PfPh196PlipY8ffk0pshqVI14uniyqesm8mbJa+csbc9Z68z2nttp8msTrj65ik7RYcS0alGn0bG07VJq+tRM0RyumSmAmTsuUlhUlGXjrClgG8y3nU7SOEtfX4rsQqRJCbWqj6agWDROWK5nz574+/uzZs0aRo0aZe90hBBCCCGEEEKkYckqrvr6+gLg6upKVFQU48eP56uvvqJkyZLkzJkz1ibk8VEUhR075IlsIYRIDbXz1+bGqBusOLWC3dd3A9CgYAO6lu+Ku7O7nbNLOUWyFeH8++dZf2E9Gy9uJEIfQZU8VehTqQ+53HOl+OsXLFjQquMihU2eDI0aJT6uShXLY9au/d/+quZkywbFi1ses3TpxFev5k1/D0QIkRHky5KPfFnycfvZbbNjooxR1MlfJxWzSv969erF4sWL2bt3LzNnzmSYNXtrCyGEEEIIIYQQr1DUZPQW1Gg0cfaLU1XVoj3koscZrFnFYWehoaF4enoSEhKCh4eHvdMRQghhJzIfWM+h3jONJvFVnxER4OxsWTyjEUqWNLXpje/nGo0GPvkEvvrK8hx37IDGjRMeM3MmDB1qeUwhhMOYum8qY7aPibc1sFbR4uXuxfWR13HSOtkhu5Rlz/ng8ePHvPPOO+zZs4devXoxatQoypcvn6o5JIVDzaFCCCHsRuYD68l7JoQQAlJmPkjWylWIfx852QtOCCGEEA5r3z7TalNzBg60vLAKpuLp+vVQvz48fmwqtkYfNxqhSRP47DPrcmzUCAYNgnnz4j/fvLkUVoVIw0bVGsXB2wdZc24NGkWDUTX9f0OraMnsnJmN725Ml4VVeypSpAgAer0eVVVZsmQJS5Yswd3dnezZs1vUdenKlSupkaoQIgkCbgcw5K8hHL17FBUVnUZHs6LNWNh6IV6ZveydnhBCCCGESGeSVVw1Rt88FPZlMEBICGTObN3NYCFSUKQhkueRz/F08USr0do7nXgZjUZuht7E3dmdnG457Z2OyGDGjBmDr68vdevWxc3Nzd7pZCy1asGlS1C5Mjx//t9xnQ4WLIDeva2PWaYMnD4Nc+fCsmWmebl4cRg8GN591xTbWnPnQoMGpsLs1aumY3nzwpgxUlgVIo3TaXT83uF3Vp9dzZyAOZx9dJbMzpl5t9y7DKk+BB8PH3unmO4EBQXFdFhSFCXmgeDnz5/z/NW5wAxLujMJIexj/fn1tFvVLlY3AL1Rz6ZLmyj4Q0EuDL1AAc8CdsxQCCGEEEKkN8lqC5zROFwriYcPTXvH/fwzPHtmunHboYPpJmzZsvbOTmRQZx6cYeLeifxx9g/0Rj1ZnLPwXpX3GPvm2FTZ39ISzyOf0/mPzvhd8cOgmlp4erp48lHtj/i03qd2zk6kBbaYD6Jb6zs5OVG9enV8fX3x9fWldu3aODmlv9VKDjeHCiGEsAt7zQeFChVKdoH02rVrNsrGOjKHCmGe0Wgk06RMRBoizY4plaMU54aeS8WshEgZMh9YT94zIYQQkDLzgRRXreBQE/K9e1CzJty6FXt/N50OnJxg+/aEWx4KkQL239xP46WNiTJGoTfqY45rFS0+Hj4c6HeAPFny2DFDCI8MJ/+M/Dx+8Tje813LdWX5O8tTOSuR1tiquBrt1Zu9rq6u1K5dG19fXxo2bEiNGjUSbVWYFjjUHCqEEMJuZD6wnrxnQpg389BMhm8dnui46yOvy+pVkebJfGA9ec+EEEJAyswHaf9ubUY1ahTcvh27sAqg10NEhKkF4evnhEhBBqOBd/98lwhDRKzCKoBBNXAr9Baj/UbbKbv/9FzX02xhFWDF6RUcunUoFTMSGdXhw4eZMmUKb731Fm5ubqiqiqqqvHjxgp07d/LZZ59Rp04dsmXLRsuWLZk+fTqBgYH2TlsIIYQQQgiH8feVvy0at+XSlhTORAghhBBCZCTJ2nP1dXfv3mXHjh2cPXuWx48fExUVxcKFC235EgJM7YBXrzYVUuNjNMKNG7BtGzRrlrq5iQxr+9Xt3Ai5Yfa8QTWw+txqfgz70a7tgTdc2JDomDHbx+Df2z/lkxEZWrVq1ahWrRoff/wxer2eQ4cOsXPnTnbu3MnBgweJiIgA4NmzZ2zZsoUtW0w3hLJnz079+vVp1KgRgwcPtue3IIQQQgghhF05a50tGueqc03hTIQQQgghREZik5WrwcHB9OzZk4IFC9KrVy+++eYb5s+fz+LFi+OMHTRoEM7OzhQtWtQWL50xXbxovrAaTauF06dTJx8hgFMPTqFVtAmO0Rv1XAy+mEoZxfVS/5IoY1Si4y4/vpwK2QjxH51OR506dfj888/ZtWsXT58+Zfv27XzyySfUrFkTrVYbs7I1ODiYNWvWMHToUHunnT7cuwcBAXDlir0zSV1Pn8KRI3D2rOmhLCGE3QSHB3PkzhHOPzqP7NgihBDWea/Ke4mOUVDoWKZjKmQjhBBCCCEyimQXV69du0blypVZvnw5er0+5uavOYMHD0av1xMUFMSePXuS+/IZk5tb4mOMRsiUKeVzEeJfbk5uGNXEb9BncrLff5fOGsuearb06WchUoqLiwu+vr58/fXX7N+/nytXrvDee++h0+li7c8qkuH8eWjVCvLmhRo1oFgxqFoV/rastVya9eAB9OkDXl5QvTqULWv63uN5IE4IkbJuh97m3dXvkvu73FRfUJ3Ss0tTenZpVp1eZe/UMoSAgAC+/vprunbtSrNmzWjUqFGcMY8ePeLOnTs8fmx+SwkhhH01L94cLzevBMc0LdoUN2cL7qMIIYQQQghhoWS1BTYYDLRu3Zpbt24B0LVrV3r16sWlS5fMrqipWLEiJUqU4NKlS/j5+VGvXr3kpJAxVagAPj7w7/tuVqtWqZOPEEDLEi0ZujnhlXT5PfJT0btiKmUUl0ajwSeLD7eeJfx3p0OZDqmUkRDxCw8PZ+/evTFtggMDAzH+u7ow+gEmKbImw/nzULMmPH8Orz4QFhhoaqe/ejW0b2+39FJMcDDUrg1BQbH3Zb92zVRwvXsXxo61W3pCZCR3nt2hxs81ePD8AXr1v440F4Mv0uXPLjwKf8T7Nd63Y4bp1+XLl+nbty/79u2LOaaqarzz6uTJk5kxYwa5cuXi9u3baLUJd2kRQtjH4f6HKTunLGFRYXHOlcxRko1dN9ohKyGEEEIIkZ4la+Xq0qVLOXPmDIqi8MMPP7Bs2TKaNGlCvnz5EryuYcOGqKrKoUOHkvPyGZdWC59/bv68RgPdu0OBAqmXk8jwCngWoHuF7mgU8/9b+bTup2g19r0pNbHRxATPO2mc+LL+l6mTjBD/ioqKYvfu3YwbN466deuSPXt2WrRowbRp0zh69CgGgwFVVSlVqhRDhgxh9erVPHz40N5pp12jRpkKq68WGOG/9rj9+0NkZOrnldK++SZuYfVVn30GN2+makpCZFTj/cfHKawCqJge+BjlN4rg8GB7pJauHTt2jGrVqrFv376YjkuJdV1SVZWHDx/yd3rvbCBEGlYwa0Eef/yYz+p+RgHPAmRzzUapnKX4pfUvnB96Hp0mWesKhBBCCCGEiCNZP2H++eefALz55psMGzbM4uvKlSsHwMWL9tt7Mc3r39+0T9yXX5qKqdFPWuv10Lo1/PSTXdMTGdNPLX/iWeQz1p1fF/MBVlVVjKqRcfXHMaDqADtnCD0r9uTcw3NM2TclzjlnrTN7eu+RllEiVRw6dChmZer+/ft5+fIlQKybvEWKFKFhw4b4+vri6+uLt7e3vdJNP27dAj+/2CtWX6Wq8PgxbNwI77yTurmlJIMB5s83X1gF088Sixcn/ACXECLZwqPCWXpyaZzC6qsMqoHlp5Yz/I3hqZhZ+vbixQvatm1LaGgoOp2Ojz/+mF69enHixAk6deoU7zXFihWjUqVKnDhxgm3bttG8efNUzloIYSlnnTNf+X7FV75f2TsVIYQQQgiRASSruHr8+HEURaG9la3zcubMCUBwsDyNnWSKAl98Ab16mW6EXrsGOXLAu+9CtWr2zk5kUJmcMrG281qO3DnCb6d+I/hFMIWzFqZ3pd4UzFrQ3unFmNx4MoOqDeKDvz/g5P2TOGmc6FS2E2PfHIuzTvZbFamjVq1aMS0IowuqPj4+NGzYMKagWkA6ENheUJD5wmo0rRauXk2VdFJNSIjpKyGKAleupE4+QmRg95/f56X+ZYJjtIqWq0/S2f+H7GzBggXcunULRVFYtWoV7dq1A+Ds2bMJXle3bl0CAwM5cuRIaqQphBBCCCGEECINSFZxNbo46uPjY9V1Go2pbWj0/nEiGQoWhHHj7J2FELFUy1uNankdu8hfMGtBVndabe80hACgTp06fPXVVzRo0MDeqaR/2bIlPsZohKxZUzyVVOXuDjqdqcNFQix5f4QQyeLp6pnoGKNqJKtr1pRPJgNZv349iqLQvHnzmMKqJUqXLg2Y9moVQgghhBBCCCEgmXuuuru7AxAeHm7VdXfv3gUge/bsyXl5IYQQIk2L3utt//79NGrUiNKlSzN06FD+/PNPHj9+bO/00qcyZaBUqf/a6cdHpwMrbrynCS4u0L696XszR683dcAQQqSo7Jmy06RIE7SK+X3oDaqBLuW6pGJW6d+ZM2cAePvtt626Lvoz69OnT22dkhBCCCGEEEKINCpZxdX8+fMDcPLkSauu27t3LwDFixdPzsuLlBQaCrdvQ2SkbeKpKjx8aNonVlYsZwjPI59zO/Q2EfoIe6dilsFo4O6zuzx+Ybsi1u2Q22y+tJlrT67ZLKZIn/7++2/+97//UaNGDTQaDaqqcuHCBebOnUunTp3w8vKicuXKfPjhh2zevJnnz5/bO+X0QVFg8mTzrYEVBUaPhn+3MEhXPv3U1PJYE8+Pf1otvP02VK+e+nkJkQGNbzAeRVFQiPugh0bR0LV8V0rlLGWHzNKvJ0+eAODl5WXVdWpireSFEEIIIYQQQmQ4ySquNmjQAFVVWblyJZEWFuGuXbvGhg0bUBSFhg0bJuflRUo4cACaNze1Q/TxgezZYfhwePQoafFU1bQnbNmy4OUFefJAkSIwYwYYDDZMXDiKY3eP0WZlGzyneOLzvQ/ZvsnG4E2Dufvsrr1Ti/FS/5IJuyeQ57s85J2elxzf5qDGghqsP78+yTH/PPsnHpM98Jnhw9sr3qbIj0Vwm+jGzEMzbZi5SE8aN27MpEmTOHjwII8fP2bjxo2MGjWKChUqAKbW+SdOnOD777+nVatWZM+enTp16vD555+za9cui+ddEY+2bWHpUsiSxfR7nc5UVNXp4KOPYNIku6aXYipUAD8/8PY2/V6n+6/Q+s47sGpVwit6hRA2Uyt/LTZ02UAOtxwA6DQ6NIoGBYWeFXvyS+tf7Jxh+uPpaWrHHBoaatV1t27dAiBHjhw2z0kIIYQQQgghRNqkqMl4FPfEiRNUqVIFgAEDBjB37lzAtJ9Nu3btUBQFwysFtMePH/PWW29x7NgxnJycuHz5cszq17QgNDQUT09PQkJC8PDwsHc6trd5M7RpYyqIvlr41GqhQAE4eNBUILXGRx/BtGmmm7Wv/qemKNCpE6xYEf8KGpEm7bq2i2bLm2EwGjCo//03pNPo8HL34mC/g+T3tO/f+Qh9BG8te4t/bvyDUf1vFbVG0WBUjcxoOoMRNUdYFXNp4FJ6re9l9vxndT/jK9+vkpyzcDwpPR88fvwYf39/du7cyc6dOzl//nzMOeXf4perqythYWE2f+2U4pBzaHg4rF0LV69CjhzQoYP181xapNeb5vxTpyBTJtPcX7SovbMSIkOKNESy8cJGzj06RxbnLLQr3Y4CngXsnVaKstd8UKNGDY4ePcrgwYOZNWtWzHFzn12jtWjRgq1bt9KkSRP8/PxSLd9XOeQcKoQQItXJfGA9ec+EEEJAyswHyapqVaxYkd69e6OqKvPnz6dZs2Zs376dZ8+exYwJDw/n/PnzfP/991SsWJHjx4+jKAojRoxIU4XVdO/lS+jRw1RUff2mgsEAN2/C2LHWxTxwwFRYhbjtF1XVtELmzz+TnrNwKAajge5ru6M36mMVVgH0Rj0Pwh4w2m+0nbL7z+yA2XEKq0DM70f/PZqgp0FWxey3oV+C57/e+3W8N+uEMCd79uy0b9+eWbNmcfbsWa5du8Z7772H7t/9MlVV5eXLl3bOMh1wc4Nu3eDzz2HIkIxRWAXTitXWrU1tgkePlsKqEHbkrHXmnTLv8Fm9zxhRc0S6L6zaU6NGjVBVlVWrVlm8ejUwMBA/Pz8URaFx48YpnKEQQgghhBBCiLQi2UsG586dS/369VFVlW3bttG0aVN69eoVs7ImS5YslC1blg8//JDbt2+jqipvvfUWkydPTnbywobWroXHj83vQafXw/Llpr1YLTVvnukGrjlaLcyebV2ewmFtvbyVO8/uxClaRtMb9aw9v5b7z++ncmaxzQ6YneDeWQoKC48ttDjeilMr0Kv6RMd9tP0ji2MKoaoqAQEBTJkyhbfeeouyZcuycOFCKdILIYQQSdS/f390Oh2PHz+mV69e6PUJ//x29epVOnTogKqquLm50bdv31TKVAghhBBCCCGEo0ug8mUZZ2dntm/fzmeffcYPP/wQayWNoiixihguLi4MHz6cSZMmodVqk/vSwpbOnQMnJ4iKMj8mIgKCgkx7tlni1ClTUdYcgwFOn7YqTeG4zj48i1bRxlm1+iqDauDS40t4Z/ZOxcz+ozfqufrkaoJjjKqRs4/OWhzzr4t/WTRu3819FscUGdPp06fZuXMnO3bsYM+ePbFW1bw+l9aqVQtfX197pCmEEEKkSUWKFOHDDz9kypQpbNiwgUqVKjFy5MhYXZfOnj3LjRs32LJlC7/88gthYWEoisK4ceNkz1UhhBBCCCGEEDGSXVwF0Gq1TJ48mdGjR7Nq1Sr27NlDUFAQT58+JXPmzPj4+FC/fn26dOlCvnz5bPGSwtbc3cEY/4rDWDJntjxmlixx91pNTjzh0DI7Zza7avX1cfaiVbQ4a52JNESaHaNRNFblmD1TdovGebjI3h4ititXrsTsqbpr1y4ePnwYc+7VYqqTkxPVq1enYcOG+Pr6Urt2bVxcXOyRshBCCJGmTZw4kZs3b7J8+XLOnTvHwIEDgf/2My9fvnzM2Oi5uG/fvnz44Yepn6wQQgghhBBCCIdlk+JqtFy5cjF06FCGDh1qy7AiNbRrB//7n/nzigJly0LhwpbH7NgR9u41f16rhS5dLI8nHFrrkq0ZumVogi13C3oWpIK3hSufU4CiKLxT+h3+OPsHemP8q6oNqoH2pdpbHHN8w/HMCpiV6LgpjaZYHFNkDMWLF4+5mfvq3xuNRkOVKlXw9fWlYcOG1K1bF3d3d3ulmb5NnAhffQWRkaDRQKtWpjb5Qog0T1VVdl/fzZ9n/+R51HNK5ShF70q9k9U946X+JX+c+YM91/cAUK9gPTqW7YirztVWaTskg9HAlstb+OviX0QYIqicuzI9KvYgq2tWe6dmNUVR+PXXX3nzzTeZMGECd+/eNTs2V65cfPnllwwePDgVMxRCCCGEEEIIkRYoakKVEBFLaGgonp6ehISE4OGRDlehde4Mq1ebX8G6ejW8847l8UJDoXRpuH/f1AL4VVotuLnBmTOQP3/ScxYOpf+G/vwS+IvZFay/tP6FPpX7pHJWsQXeC6TGghrojXpUYv/vT6foKJWrFMcHHkensfzZkwpzK3DqwSmz573cvLj/kX33mhW2ZYv5QKMxbXuuKAply5bF19cXX19f6tevj6enpy3TdQgONYdGRYGHB7yylUEsp05BuXKpm5MQwmYev3hM699as+/mvpj53Kga0SgaZreYzYCqA6yOeeTOEVosb8HD8IcxMfVGPV5uXmzutpmqeava9HtwFDdDbtJ0WVPOPToX830bjAYyOWViRfsVtCnVxuqYjjIfREZG8vfff5vtutS8eXPc3Nzslt+rHOU9E0IIYV8yH1hP3jMhhBCQMvOBFFetkO4n5PBw6NYN1q0Dnc60WtVgMBVCZ8yAIUOsj3nxIjRvDlevmvZ0BdNNbS8v2LgRatSw5Xcg7CxCH0HfDX1ZcWoFOo0OBQWDakBBYVKjSXxc52N7pwjAlktb6Ly6M88in+GkcUJFRW/UUyVPFTa9u4k8WfJYFc9gMFD4x8LcDL0Z55yniye3Rt+yaztkYXu2mA+GDBlCw4YNadiwITlz5rRxho7HoebQnDkhONj8eUWxrFW+EMLhqKqK71Jf9l7fa3Yf+E3vbuLtEm9bHPPe83uUnlWaZ5HP4sTUKlqyuGTh/Pvn7banfEqJMkRRbm45rj6+il6N3fFDQUGr0XKg3wGq5a1mVVyHmg/SCHnPhBBCgMwHSSHvmRBCCEiZ+cCmbYFFGufmZmqHGBgIq1ZBSAgUKwY9e5puRCdFiRKmAutff8GOHaab1bVrm1bAOjvbNH1hfy46F5a3X84nb37Cb6d/Izg8mMLZCtOzYk9yZ85t7/RiNC/enLsf3OW3079x/O5xXHQutCrRigaFGsS0abWGVqvlxqgbbLq4iVFbRxH8IpgszlkY32A8vSv3tv03INKFOXPm2DuFjCkkJOHCKpj2Cp8yJeF2+UIIh3T49mH8g/zNntcoGr7e+7VVxdX5R+fHW1gF03YCoRGhLDi2gM/qfZaUlB3W+gvruRh8Md5z0d0/pu2fxsoOK1MzLSGEEEIIIYQQwu4sWrnat2/flHlxRWHhwoUpEjslyNNOQgghQOaDpHCY96xLF9MDRInJmhWePEnxdIQQtjV2+1imHZhmdm/1aA8+fEAu91wWxSw/tzynH5xOeIxXeU4OPmlxnmlB9zXdWXl6pdkVwABOGiciPouw6uE0h5kP0hB5z4Swn0fhj/AP8kdv1FMtbzWKZS9m75REBibzgfXkPRNCCAF2XLm6ePHiJK3mskRaKq4KIYQQIo179MiycVFRKZuHECJFhEeFo5D455YX+hcWxwyLDEt8TFTiY9Ka8KhwjGrCLdKjjFEYVSNaRZtKWQkhROp4EfWCkX4j+eX4L7Ee2GlcpDGL2izCx8PHjtkJIYQQQgh7s7gtcEpszZpSBVshRPqjqio3Q2+iN+rJ75EfJ62TvVOK1+kHpzly+wjlvctTNW9Ve6cTL4PRELM/bH6P/Gg1ckNUZCB9+pja1CemePGUz0UIYXPlvcsnumrV08XTqu0KKuepHPMzSHx0Gh1VclexKs+0oLxXeTZc2GB25aqCQvEcxR3u5whfX98UiasoCjssmT/iMXfuXObOnUtQUBAAZcuW5YsvvqB58+Y2zFAIYStG1Uj7Ve35++rfcR4y8b/mz5u/vMmxgcfInim7nTIUQgghhBD2ZlFx9dq1aymdhxBCxEtVVRYHLmbyP5O59PgSADky5eD96u/zSd1PcNG52DlDk6WBSxn016BYK2GcNE6MbzCesXXH2jGz/xiMBn449APTD0zn9rPbAPh4+DC65mhG1ByBRtHYOUMhUkG3btC9e+Lj/P1TPBUhhO11KdeFUX6jCIsMi9kX9FVaRcvAqgNx1jpbHHNItSGsObfG7Hm9Uc/g6oOTlK8j61elH1/v/TrBMUOrD02lbCzn7+9v84d4VVVNVkwfHx+mTJlC8eLFUVWVJUuW0KZNG44fP07ZsmVtmKkQwha2X93O1itb4z2nV/XcDL3J7MOz+bz+56mcmRBCCCGEcBQW7bkqTKRPvxCpb+z2sUzZNwUFJdZNUo2ioUGhBmzptsWqG6QpYe7huQzZMsTs+Q9qfsC0ptNSMaO4VFWl59qeLD+1PM7NZgWFbuW7sbTdUukoYCGZD6znUO/ZggUwYID5802awN9/p14+QgibWn9+Pe/8/g5ArFWXWkVLee/y7Om9hywuWSyOp6oqI7aOYObhmWjQYMS0iin618PfGM6MpjPS5Rw678g8Bv81GK2ijfVeKig0KdqETe9usrqbSErPBxpNyjwspigKBoP5/WetlT17dqZOnUq/fv3inIuIiCAiIiLm96GhoeTPn98x5lAhMoBua7rx++nf0avmOyEU8CzA9ZHXUzErIRzsM1UaIe+ZEEIISJn5QJYpCSEc1ol7J5iybwpAnIKgUTWy69ouFh1fZI/UYhm2dViC5787+J1Nb8YlxeZLm1l2alm8q3hUVJadWsaWy1vskJkQdtC/PyxbBrp4Gni8954UVoVI49qUasPePntpXrx5TFeGnG45+bTup+zts9eqwiqYimo/NPuBxW0WU8arTMzxsl5lWdJ2SbotrAIMqjaIrd228maBN2OO5ffIz7dNvk1SYTU1GI3GFPmy1c9yBoOBlStXEhYWRq1ateIdM3nyZDw9PWO+8ufPb5PXFkJY5nbo7QQLqwAPwh6kUjZCCCGEEMIRWbznqhBCpLb5R+ej0+gS3DttzpE5DKw2MBWzim1p4FKze5G9aqTfSGa2mJkKGcVv3pF5cVadvEqraJl3ZB4tirdI5cyEsJNu3UxfISGwaxdUqQIFCtg7KyGEjdTKX4uN727kpf4lL6Je4Onqmaz294qi0KtSL3pV6sWziGcAVhdp06qmxZrStFhTwqPCiTRE4unimW6LySnp1KlT1KpVi5cvX5I5c2bWrl1LmTJl4h07duxYRo8eHfP76JWrQojU4ePhk+jnUG9371TMSAghhBBCOBoprgohHNa5R+cS/ECronIx+GIqZhSX3xU/i8YdvnM4hTNJ2JmHZxIsAhtUA2cenEnFjIRwEJ6e0LatvbMQQqQQV50rrjpXm8bMKEXV17k5ueHm5GbvNNKskiVLEhgYSEhICKtXr6ZXr17s3r073gKri4sLLi4udshSCAHQu1Jvlp9abva8RtHQv0r/VMxICCGEEEI4GmkLLIRwWB4uHomuMsnsnDmVsolfLvdcFo3L6pI1ZRNJhKeLZ+JjXBMfI4QQQgghrOfs7EyxYsWoWrUqkydPpmLFivzwww/2TksIEY9GhRvRsnjLeD+L6jQ6CnoWZEj1IXbITAghhBBCOAoprgohHFansp0wqkaz53UaHe+WezcVM4prfP3xFo2b+tbUFM4kYV3KdUmwUK1RNHZ/L4UQQgghMgqj0UhERIS90xBCxENRFFZ3Ws3gaoNx0f63ilxBoWnRpuzru49smbLZMUMhhBBCCGFvUlwVQjisd0q/Q8kcJdFp4nYw1ypaXLQujKw5MvUTe4VnJk+q5qma4BgfDx8qeFdIpYzi916V98jplhOtoo1zTqtoyeWWi35V+tkhMyGs9PIlREXZLp7BANeuwYsXtosphHAYeqOe8KhwVFW1WczQl6GEvgy1WTyR/o0dO5Y9e/YQFBTEqVOnGDt2LP7+/nTr1s3eqQkhzHDRuTCrxSzufnCXdZ3X8UfHP7g64iqbum4iT5Y89k5PCCGEEELYmRRXhRAOy0Xnwo6eO2IKkzqNDieNEwA53XKyved2imQrYs8UATjU7xDFsxeP91zOTDm5MvxKKmcUVw63HOzuvZtCWQsB4KRxinkvC2UthH9vf7Jnym7HDIVIgNEI8+dD6dKQKRM4O0PDhrBlS9JjHj0K+fKBTgdFioCbG2TJAgsW2C5vIYTdHL1zlA6/d8D1a1fcJ7mTb3o+Ju2dRHhUeJLiGY1Ghm8Zjvskdzy/8cTzG0/cJ7kzYssIjEbzXTaEAHjw4AE9e/akZMmSNGrUiICAAPz8/GjSpIm9UxNCJCJbpmy0KdWGDmU6xHyWEkIIIYQQQlFt+Rh3OhcaGoqnpychISF4eHjYOx0hMgxVVdl7Yy9+l/2IMkZRPW912pZqi5PWyd6pxbInaA/vb36fB+EPyOqSlSmNp9CudDt7pxWLwWjA74ofe67vAaB+wfo0LdY00b1tRWzWzAdLly5NsTx69uyZYrFtLclzqNEI3bvDb7+BokD0jy1arWnV6YwZMGKEdcns2QP165s//9ln8NVX1sUUQjiMzZc202ZlG8C0cjWaRtFQLU81dvbaibuzu1UxayyoQcCdgPjP5a3Bof6Hkp5wBiOfqawn75kQQgiQ+SAp5D0TQggBKTMfSHHVCjIhCyGEAOvmA41Gg6IoNs9BURT0en3iAx1EkufQ5ctNxVVzFAXOn4cSJSyPmTkzhIUlPCYiwrRCVgiRpoRFhpF3el6eRTxDJe7HHK2iZUydMUxsNNHimDMOzmCU36gEx/zY7EeGvTHM6nwzIvlMZT15z4QQQoDMB0kh75kQQghImflAlioJIYQQKUxV1RT5yhBmzgRNAj+uaDTw00+Wxzt8OPHCKsCgQZbHFEI4jFVnVhEaERpvYRXAoBqYe2QuUQbL927+bv93iY75dv+3FscTQgghhBBCCCFE2qazdwLCBi5dghMnoGBBqF7d3tkIAcCt0Fs8fvGYfFnykcMtR7LjGVUjl4IvoTfqKZq9KK4612THDI8K5+qTq7hoXSiWvZhNVheee3iOMw/PUCRbEarkqZLseCLtW7Rokb1TSNtOnDC1BjbHYIDAQMvj/f67ZeMOHLA8phDCYZy4dwInjRNRRvPF0ycvn3D3+V0KeBawKOa9sHuJj3me+BghhBBCCCGEEEKkD1JcTct27oSePeH27f+OZckCEybAyJF2S0tkbP5B/ny641P239oPmNrvtSvVjimNp1A0e1Gr46mqypyAOXyz7xtuht4EwMPFg4FVB/Jlgy9xc3KzOmZoRCif7/ycn4//THhUOABFsxXlk7qf0KdSnyQVWTdc2ED/jf15EPYg5lhWl6xMfWsq71V5z+p4Iv3o1auXvVNI21xd4eVL8+cVBTJlsjxe1qyWv64QIs3J5JTJ7KrVV1nzkJZW0aIn4TbsWkVrcTwhhBBCCCGEEEKkbWm2LfCXX36JoiixvkqVKmV2/OLFi+OMd03LN063bYPGjWMXVgGePYNRo+Dzz+2Tl8jQNl7YSKOljTh4+2DMMYNqYO35tVRfUJ1LwZesjjnabzRDtwyNKayCqTj63YHveOvXt4jQR1gV73nkc+ovrs/sgNkxhVWAK0+u0G9DP8bvHm91jqvPrqbNyjaxCqsATyOe0n9jf4vaCQohzGjXDnQJPAumqtCmjeXxPvjAsnGffGJ5TCGEw2hVohV6o/lCqEbRUD1vdbzcvSyOWSNfjUTH1PSpaXE8IYQQQgghhBBCpG0WrVxdunRpiiXQs2fPJF9btmxZtm/fHvN7XUI3XwEPDw8uXLgQ83tbtAC1m27dTDeUzZk4EcaOBTfrV/UJkRRRhij6buhr2gvytRUjBtVAaEQoo/xGsanrJotjHr1zlBmHZsR7zqga2X9zPz8f+5n3a7xvccwfD/3IyfsnMarxtxkdv3s8Xct3pUSOEhbH7Lu+b4Lnx2wfw4iaI9BppFmAEFYbPRqWLTOtUH193tNqwdsbuna1PF6mTFCpUsKthN3coGPHpGQrhLCz2vlrU9unNoduH8KgGuKcN6pGPq37qVUxZzSbQdX5VRMe03SGVTGFEEIIIYQQQgiRdll0p793794pUohUFCVZxVWdTkfu3Lmtej1rxjusY8fg4cOEx6gqjB8P33yTOjmJDO+vS3/xKPyR2fMG1cDmS5u58+wOebPktSjmgmML0Gl0Ca5AmXtkrlXF1blH5potrIKprd/CYwv5pollf3e2XNrCs8hnCY4xqAZ+OPgDH9S2cMWcEOI/5crB2rXQqRO8eAEajanQqtdD3rzw99/g7m5dzCNHTPuUv979AcDJCU6ftk3uQohUpygK699dT4vlLQi4E4BOo4v14NeMpjNoU8qK1e5AlTxVWNBqAQM2DojzAJmCwvxW86mUp5KtvgUhhBBCCCGEEEI4OIuXUakJrZK0k0uXLpE3b15cXV2pVasWkydPpkCBAmbHP3/+nIIFC2I0GqlSpQqTJk2ibNmyZsdHREQQEfFfy9HQ0FCb5p9kBw8mPgbk5rBIVZeCL6FVtPGuEommonL1yVWLi6sXHl1IsLCqonLlyRWLc9Qb9dwKvZXgGKNq5PKTyxbHPHTrkEXjjt87bnFMIcRr3n7bVAhdsgQCAkwF0KZNoX17cHa2Pp5WC7duweLF8Nln8OSJaY/Vfv1g8mTTeSFEmpXTLScH3zvI9qvbWX12Nc8jn1M6Z2n6Vu5LPo98SYr5XpX3aF2iNR9t+4h/bvwDQN2Cdfm28bd4Zba8xbBIeRMmTEix2F988UWKxRZCCCGEEEIIkXZYVFxdtGhRSudhtTfeeIPFixdTsmRJ7t69y/jx46lbty6nT58mS5YsccaXLFmSX375hQoVKhASEsK0adOoXbs2Z86cwcfHJ97XmDx5MuPHW7//YorLk8eycdmypWweQrwiq2vWBFeERvN08bQ4ZrZM2dAomgTjerh4WBxPq2jJpMvEC/0L82M0Wqty9M7sbdG4HJlyWBxTZDz79+9nyZIlHDx4kFu3bhEaGorRmPDfJ0VR0OvNP3yQ7mTNCiNG2DZm796mLyFEuqNRNLxV9C3eKvqWzWJ6ZfZiSbslNosnUsaXX36ZYtu/SHFVCCGEEEIIIQSAojriktQkePr0KQULFmT69On069cv0fFRUVGULl2ad999l6+++ireMfGtXM2fPz8hISF4eFhe0LE5o9G0wiYqKuFxp09DAitzhbClB2EPyDc9n9mVpgoKJXKU4Nz75yy+4fX7md/pvLqz2fNaRcvwN4Yzvel0i/Psu74vv578NcEVsVu7baVpsaYWxYvUR5JpUqZEC8u3R90mr4dlK3aF4wsNDcXT0zPZ80F4eDh9+/bljz/+AKzrEqEoCgaD+ZXijsZW75kQQoi0LaXnA41GY/OYYN95V+ZQIYQQIPNBUsh7JoQQAlJmPrC4LbCjy5o1KyVKlODyZcvaeTo5OVG5cuUEx7u4uODi4mKrFG1Ho4Fhw2B6AgWlKlWksCpSlZe7F8NqDGPGwRlx9iMDUwvfr32/tmolQbtS7SjnVY7zj87HKYZqFS2ZnTMz4g3rVrJ9XOdjVp5eiVE1ximIahUtNfLVoEnRJhbHc9Y507NiTxYHLjY7pmGhhlJYFfHq1q0bGzZsQFVV3N3dKV++PAcPHkRRFMqUKUOmTJkICgri0SPTfsaKolC1alXcrd1jVAghhMggdu3aZe8UhBBCCCGEEEKkc+mmuPr8+XOuXLlCjx49LBpvMBg4deoULVq0SOHMUsh330FwsGn/uddVrAgHDqR+TiLDm9pkKgbVwKzDswBTsVJv1OOqc+XH5j/SoUwHq+I5aZ3Y3mM7HX7vwD83/0GraE2tUI168nnkY23ntRTMWtCqmKVylmJbj210+KMD957fw0njhFE1YlAN+Bb2ZVWHVWgU61Y8LGqziJCXIaw9vzbOudo+tfm7x99WxRMZw/bt21m/fj2KotC2bVuWLFlClixZYlbcTJw4kdatWwMQEBDAuHHj2Lp1KxEREfzxxx8ULGjdf/tCCCFERlC/fn17pyCEEEIIIYQQIp1Ls22BP/zwQ1q1akXBggW5c+cO48aNIzAwkLNnz5IrVy569uxJvnz5mDx5MgATJkygZs2aFCtWjKdPnzJ16lTWrVvH0aNHKVOmjEWv6ZCtJO7cgU8+gcuXIWdO+PRTqF7d3lmJDO5W6C3+OPMHwS+CKZy1MJ3KdiKLS9y9kK0RcDsAvyt+RBmiqJGvBs2KNUOr0SY5nt6oZ+OFjRy/dxwXrQstS7SkYu6Kycrx+tPrfLLjE66HXMfb3ZvxDcZTzrtcsmIKx2SL+aBnz54sW7aMvHnzcvnyZVxdXQFTO0NFUVi7dm1McTXaqFGj+OGHH6hYsSKHDh3C2dk52d9Lakn2e2Y0wpw5sG0b6HTQrx8k9wGphw+hTx+4cgWyZ4cff4SqVZMX88EDWL8enj6F4sXh7bfBySl5MYVwMEbViH+QP8fvHsdF50KL4i0okq1IsmKGR4Wz/vx6boXeIpd7LtqVaoenq+V7oMfn2N1jTNs/jdCIUKrkqcIndT/BVeearJhf7/maVadXAdC5XGc+q/dZsuKlhOgHvh6GPSS/Z35al2yNm5ObvdOK4ZCfqRycvGdCCCFA5oOkkPdMCCEEpMx8kGaLq126dGHPnj0EBweTK1cu3nzzTSZOnEjRokUBaNCgAYUKFWLx4sWA6Yb0mjVruHfvHtmyZaNq1ap8/fXXVK5c2eLXlAlZCCEE2GY+KFGiBFeuXGHkyJF89913Mceji6tr1qyhTZs2sa4xGo2UK1eOCxcuMHv2bAYNGpSs7yM1Jes927QJ3nkHIiNjH8+ZEw4fhsKFrU/o7bdh8+a4x/PnNz2wZG3h2mCAjz6CmTNNv9ZoTP/OmRN++QVatbI+RyEc0LG7x+i8ujOXH19Gq2hjWuy/U+YdFrVZRGbnzFbHXHR8ESP9RhIaERoT00Xnwpf1v+TjOh9btaUAwPPI59RYUINzj87FOq5RNExpNIWP6nxkdY6bLm6izco2cbYU0Cga1ndZT8sSLa2OaWuqqvLNvm8Yv3s8EfoINIoGg2rAw8WDGU1n0KdyH3unCMhnqqSQ90wIIQTIfJAU8p4JIYSAlJkPrOt9mYD9+/czcOBAKlasSI4cOXByckKr1Sb4pdMlvSvxypUruXPnDhEREdy6dYuVK1fGFFYB/P39YwqrAN9//z3Xr18nIiKCe/fu8ddff1lVWBVCCCFs6d69ewBUqFAh1vHoIkJEREScazQaDd27d0dVVX7//fckv/bcuXOpUKECHh4eeHh4UKtWLbZs2ZLgNX/88QelSpXC1dWV8uXLszm+wmRKOHYMWreOW1gFePQIypeHly+ti9mlS/yFVYCbN6FYMevzHD0aZswAvR5U1VRYBVML/7Ztwd/f+phCOJgrj6/QYHEDrj25BoBBNaD++8/ac2tps7IN1j63+dup3+i7oS+hEaGxYr7Uv+R/O/7Hdwe+SyRCXJXmVYpTWAXTituPt3/MksB4ttVIwMVHF2n1W6s4hdXomK1+a8XFRxetztPWpu2fxtgdY3mpf4mKikE1/X8oNCKUvhv6svL0SjtnKIQQQgghhBBCpA/JLq6Gh4fTpUsX6taty88//8ypU6d48uQJBoMBVVUT/RI2cOwY/Pwz+PnZOxPzHj+Gr7+GcePg2jV7ZyNEhvZS/5Kjd45y9M5RXuqtLEoJm3n5b0Hw9ael3N3dAXjy5Em81xX7t/B34cKFJL+2j48PU6ZM4ejRoxw5cgRfX1/atGnDmTNn4h2/f/9+3n33Xfr168fx48dp27Ytbdu25fTp00nOwWJDhpiKleaEhcH48ZbHMxhg1aqEx9y8aVoRa6lbt2DWrPjzjD726aeWxxPCQU3bP40X+hcxRbtXGVQDO6/txD/I3+J4RtXImO1jEhwzfvd4wiLDLI65+dJmrjy5kuCYj7ZZt3K10+pOiY7p8mcXq2LaWlhkGON3J/z/wv9t/1+8BeKM7tmzZ9y+fZsbN24k+iWEEEIIIYQQQgAkfenov7p168aGDRtQVRV3d3fKly/PwYMHURSFMmXKkClTJoKCgnj06BFgWpFTtWrVmJvHIhk2bTLtFffvewtApkymPVg/c5D9n54/h4oV4erV/45NmADe3nD0KOTLZ7/chMhgIg2RjPcfz+yA2YREhADg6eLJ0BpD+aL+Fzhr087+nelB1qxZCQ4OJjw8PNbxHDlyEBYWxuXLl+O9LrroGhwcnOTXbvVai9qJEycyd+5cDh48SNmyZeOM/+GHH2jWrBkffWQqSHz11Vds27aNWbNmMW/evHhfIyIiItbq29DQ0KQlGxCQ+Jhly+DfPdYTNXeuZeNGjYJ9+ywb+8cfCZ83GmH/flPRNn9+y2IK4WBUVeXXk7+iN+rNjtFpdKw4tYKGhRtaFPPQrUPcDL2Z4Jjnkc/ZcnkLHcp0sCjmt/u+TXTMw/CHXH96nYJZC1oU8+T9k4mOOXHvhEWxUspfl/4iLCrhIvT1kOsE3A7gDZ83Uikrx2Q0Glm5ciVLlizh8OHDFs9PiqKg15v/718IIYQQQgghRMaRrJWr27dvZ/369QC0bduWO3fusH///pjzEydO5PDhwzx48IBDhw7RrFkzVFUlIiKCxYsXs2vXruRln5Ft2mTav+3VwirAixfw+efwwQf2yetVBoOpiPpqYTXa/ftQsKBpRasQIsUZjAbar2rPlH1TYgqrACERIUz+ZzLvrHoHgzHuSiSRcooXLw7A9evXYx0vV64cqqqyffv2eK/bvXs3EHfFa1IZDAZWrlxJWFgYtWrVinfMgQMHaNy4caxjTZs25cCBA2bjTp48GU9Pz5iv/EktKhotWGX17Jnl8eKbk+JjTfH68WPQai0bJ0QaZVANiRbvDEYDwS8s/7vz+IVlfyeCwy2P+eRl/Kv+X5dYUfdVKol32zFi3xWhFr+XVvz5pEcPHjygXr169OjRg+3btxMSEmJRtyXpuiSEEEIIIYQQ4lXJKq4uXboUgDx58rBixQqyZMlidmz16tXZvHkzI0aM4NSpU7Rt25bI+PZPE5bp3Tvh899/D0ldJWQrgwbBayuyYjEYoE2b1MtHiAxs3fl1/HXpL7P7xW26tIn1F9bbIbOMq1q1aqiqyvHjx2Mdb9asGQAnT57kp59+inVuzZo1rFq1CkVRqFatWrJe/9SpU2TOnBkXFxcGDRrE2rVrKVOmTLxj7927h7e3d6xj3t7eMfvGxmfs2LGEhITEfN28aXkhIxYnp8THvJZbgho0sGycNfuuFipk2ms1IVot+PhYHlMIB6PT6PB2T/jvmlajpXDWwhbHLJS1kEXjCmezIqanZTFL5SxlcUydknizH50m2Q2BksXi99KKP5/0RlVV2rdvz/79+1FVlYIFC9Kli6mds6IoNGzYkA4dOlC1alV0Ol3M8aZNm9KrVy969uxpz/SFEEIIIYQQQjiQZBVXo9v/du7cGVdX1zjn43u697vvvqNUqVKcPHmSX375JTkvn3EFBCS+okZVrduDLiUsX574mFdWOgshUs5PR39Cq5hfWadVtPx09Cez54XtNWrUCICdO3diMPy3arhbt27kyJEDgCFDhlCjRg26du1KjRo16NixY8zcOmDAgGS9fsmSJQkMDOTQoUMMHjyYXr16cfbs2WTFfJWLiwseHh6xvpKkRYvEx1jTraF1a9BZUARZtMjymJ06QTw/B8XQaqFdO/j3z1WItGpQtUEJziV6o56+lftaHK+sV1mq561uNqaCQr4s+WhUuJHFMSc1mpTomBLZS5DTLafFMZsWa5romGbFmlkcLyU0KdKEvFnyoqDEe16jaKiRtwalc5VO5cwcx5o1a9i/fz+KovD+++9z6dIlVqxYEXN+xIgR/P777wQEBHDjxg0GDhyIqqqcOnWKESNGsMiaeUEIIYQQQgghRLqWrOJq9IqVChUqxDquKKYP9a/utRbzghoN3bt3R1VVfv/99+S8fMZlyf5zAOfOpWweiXn5MvExlrR7FEIk26XHlzCo5tv+GlQDl4IvpWJGomnTphQqVAhnZ+dYLYCzZs3Kzz//jFarRVVVjh49yqpVqzh69GhMYbVv3760bds2Wa/v7OxMsWLFqFq1KpMnT6ZixYr88MMP8Y7NnTs39+/fj3Xs/v375M6dO1k5WOTnn037iZtTvDi89551MadOTfh8s2aQK5fl8bJkgZkzTb9WXitsaLXg4WH5nrBCOLBRNUdRLHsxsys5R9ccTVmvuPs2J2R2i9k4aZ3iFFg1aFAUhZ9a/oRWY0Hb7X+V9SpLm5LmO6No0LCs/TKrclzZYSVOGvOr6J00Tvz+jn0/12g1Wn5q+ROKoqB57SOeVtHirHVmVotZdsrOMaxatQqAokWL8sMPP6BNoJ177ty5mTt3LlOnTuXOnTu88847Sd87XAghhBBCCCFEupOs4urLf4tnr69GcXd3B+DJk/j3PCr2b6u9CxcuJOflM658+SwbZ82N4ZRgyf5zQohUkSNTwivmFBRyuMmqutTk4uLC1atXuXv3Lk2bxl4V1aZNG3bv3k2jRo1iiqyqqlKiRAnmzJnDggULbJ6P0WiM96EogFq1arFjx45Yx7Zt22Z2j1abypkTLl6EUq+18FQUeOstOHsWNFb+ODNypKl9/usrWBUFOneGLVusz7NfP/j9d1Ox99V4zZrBoUPWtRkWwkF5unqyr+8+ulXoFqvYmDtzbr5v+j3T3ppmdczq+aqzt89e3izwZqzjlfJU4u/uf/N2ibetjrmuyzr6V+kfp1Vv3sx5+afvP1TPV92qeJmdM3N71G3yZM4T51yezHm4Peo2mZwTeAgklbQs0RK/7n5UylMp1vE3C7zJP32s/77Tm4CAABRFoWPHjmjimTfi67r0wQcfUK1aNYKCgpg/f35qpCmEEEIIIYQQIg1I1uZAWbNmJTg4mPDX9tXMkSMHYWFhXL58Od7roouuwYm1thXxa9UKnJ0hsT1rP/kkdfIxp1Yt2Ls34TGFM+6+T0Kkph4VenDs7jFU4t44jNazguwl5khq1arFtm3b0Ov1PHr0CHd39wT3NrfG2LFjad68OQUKFODZs2esWLECf39//Pz8AOjZsyf58uVj8r+rLUeMGEH9+vX57rvvePvtt1m5ciVHjhxJvRvNPj6mbgw3bpgKn66u8M47kDlz0mOOHGn62rABdu40FT8HD07eg0EdO0KHDnD6NISEmOY4Sx+IEiKNyOGWg8VtFzO96XTOPTyHq86VirkrJmvP0Wp5q+Hf259rT65xK/QWXu5elMxZMll5zm81nzlvz2HNuTU8Cn9EvQL1KOddLsnxcmXOxZ0P7nAj5AZzj8wFYHC1wRTwLJCsPG2tcZHGHB1wlAuPLvAg7AH5PfNbvB9revfw4UMASpeO3Ro5uuvSSzNddzp37syRI0dYs2YNH374YcomKYQQQgghhBAiTUhWcbV48eIEBwdz/fr1WMfLlSvH9evXY7U5fNXu3buBuCtehYU0GvjwQ5iUwJ5StWpByeTdlEq2334z3RBPyK+/pk4uQmRwfSr34fuD33P72W30Rn2sczqNDh8PH3pV6mWn7ERCdDqdzdvvPnjwgJ49e3L37l08PT2pUKECfn5+NGnSBIAbN27EWtVTu3ZtVqxYwWeffcYnn3xC8eLFWbduHeXKJb1QkSQFCsDAgbaN2bq16ctWFAXKl7ddPCEcVPZM2alToI5NYxbOVpjC2Wz34J1Oo6NT2U42iwdQwLMAkxs5fpvvkjlLJrtAnd5ERUUB/3VZipY5c2aeP3/Oo0eP4r2uQAFTAf3q1aspm6AQQgiRQcyePZupU6dy7949KlasyMyZM6lRo0ai161cuZJ3332XNm3asG7dupRPVAghhEhAstoCV6tWDVVVOX78eKzjzZo1A+DkyZP89NNPsc6tWbOGVatWoSgK1apVS87LZ2wTJ8KQIfGfq1kT9uxJ3Xziky8f7NgR/yogRYFFi6CObW/KCSHi5+HiwZ4+e6iUuxJg2n8ten+7Srkrsbv3bjxc5IGXjGLhwoUEBQURERHBgwcP2L59e0xhFcDf35/FixfHuqZjx45cuHCBiIgITp8+TYsWLVI5ayGEECLpcuQwbX/w7NmzWMe9vb0BuHjxYrzXRe85/vTp05RLTgghhMggVq1axejRoxk3bhzHjh2jYsWKNG3alAcPHiR4XVBQEB9++CF169ZNpUyFEEKIhCWruNqoUSMAdu7cicFgiDnerVu3mA+vQ4YMoUaNGnTt2pUaNWrQsWPHmP1sBgwYkJyXF7NnQ3AwDB0KTZpA166mvecOHIi7j5y9+PqCXm9aZVuqlGk17ahREBUFvXvbOzshMpQCngU4/N5hDvY7yORGk5ncaDKH3jvE4fcOO1xbw4wqMjKSw4cPs27dOn799VfWrVvH4cOHiUysDbwQQgghElSiRAkArl27Fut4+fLlUVWVrVu3xntd9PHs2bOnbIJCCCFEBjB9+nT69+9Pnz59KFOmDPPmzcPNzY1ffvnF7DUGg4Fu3boxfvx4ihQpkorZCiGEEOYlqwLXtGlTChUqxIsXL9i+fTtNmzYFTHux/vzzz3Ts2BG9Xs/Ro0c5evQoQExhtW/fvrRt2zZ52QvInh1mzrR3FokbO9b0JYSwK0VReMPnDd7wecPeqYhXHDx4kGnTprFp06aYtoWvcnZ2plWrVnzwwQe88Yb82QkhhBDWeuONN9izZ0/M59JorVq1Yu3atVy+fJlPP/2Ur7/+OmYf1unTp7N582YURaFWrVr2SFsIIYRINyIjIzl69ChjX7k/qNFoaNy4MQcOHDB73YQJE/Dy8qJfv37s3bs3wdeIiIggIiIi5vehoaHJT1wIIYSIR7JWrrq4uHD16lXu3r0bU1iN1qZNG3bv3k2jRo3QarWoqoqqqpQoUYI5c+awYMGCZCUuhBBCpAcfffQRb775JmvXriUyMjJmvnz1KyIigj///JM6derw8ccf2zvl9CEqCpYtg7p1TW3sK1SAadNA2j4KkequPLqC91RvlPFKzJfnZE/2BiV88ywh957f40v/Lyk1qxT5pufjrV/fYt35dRhVY5JjHr97nL7r+1JwRkEKzihI3/V9CbwXmOR4InVFt7/39/fn5cuXMcc7d+6Mj48PAFOmTCFv3rzUrl0bb29vPvroo5hxw4cPT92EhRBCiHTm0aNHGAyGmJb80by9vbl371681/zzzz8sXLjQ4vvIkydPxtPTM+Yrf/78yc5bCCGEiE+K9o6tVasW27ZtQ6/X8+jRI9zd3cmSJUtKvmTGdO0aBAWZVrFWqGDaz1QIIYTDGzZsGHPmzInp6uDp6cmbb75J8eLFcXd3JywsjMuXL/PPP//w9OlTVFXlu+++48WLF8xMC10LHNWLF9CyJezcCRoNGI1w5w6MGWPqBrFnDxQsaO8shcgQ9gbtpd6SenGOh0aGUm9JPea3mk//Kv2tinni3gkaLmlISERITDH1/vP7bLu6jXfLvcuv7X5Fq9FaFXPhsYX039gfrUaL3qgH4NeTv7I4cDE/t/6ZvpX7WhVPpL6GDRvSoEEDXrx4wf79+/H19QUgU6ZMrFy5kmbNmvH8+XPu37/PgwcPYuZmgHHjxlG/fn17pS6EEEJkSM+ePaNHjx4sWLCAnDlzWnTN2LFjGT16dMzvQ0NDpcAqhBAiRaTKxpw6nY7cuXOnxktlLCdOwIgRsHv3f8dKlIBvvgFpuSyEEA5t165dzJ49G0VRcHNzY/LkyQwYMAAXF5c4YyMjI1mwYAH/+9//CAsLY86cObzzzjs0aNAg9RNPDz77DPz9Tb82vrKKLbrI2qEDBATYJTUhMpr6SxIuWA3YOMCq4qreqKflby0JjQiNtUrVoBoAWHl6JTXy/b+9+w6L4mrbAH7P7tIFFKUqdsXeG9gVe09ijzUakxA/jcY30SRiSUSNJc0SjYpJ7L1EjQZFY++9xIbYsIYiKmV3vj8mrK7sLrPANrh/ufYKzJx99plZ5DD7zDmnHkY2GCk75tkHZzF0y1CIELWF1YzXAoAhm4egXtF6qOJTRXZMsjylUondu3fr3RcSEoKzZ8/im2++wa5duxAXFwc3NzfUrVsXI0eORNu2bS2cLRERUd5TpEgRKJVKPHjwQGf7gwcP9H5ufP36dcTExKBTp07abZr/rt9UKhWuXLmCMmXK6DzHyclJ7zU1ERFRbsvRtMBkRWfPAiEhwP79utuvXgW6dQOWLbNOXkREJMu8efMASGvMbNu2DcOHDzd4Eejo6IiwsDD88ccfUCql0VZz5syxWK55SnIy8PPPukXV16WnA8ePs7hKZAHrLqyDCDHLdiO2j5Adc/OVzbiTeEdbTH2TCBGzD882aXrgOUfnGB3pqlQoMecofyfbu5IlS2LhwoWIiYnBy5cv8eTJE+zYsYOFVSIiolzi6OiI2rVrIyoqSrtNo9EgKipK79rmFSpUwLlz53D69Gnto3PnzmjevDlOnz7NEalERGRVuT5yNTU1FadPn8a9e/eQlJQEd3d3BAQEoEaNGnB0dMztl8u/PvkESEkB1G98cJQxfdXHHwNvvw04O1s+NyIiytLBgwchCAJ69eqFJk0yT4mpT5MmTdCrVy8sW7YMhw4dMnOGedS5c1KB1RiFAvj7b6BuXcvkRJRPffP3N7LarTi/At+3+15W2/2x++GgcECaJs1gm9iEWNxLuodiHsVkxdwTs0dnxOqb0jXpiLoZZXA/EREREUlGjRqFAQMGoE6dOqhXrx6+++47JCcnY9CgQQCA/v37o2jRooiIiICzszOqVNGdGaRgwYIAkGk7ERGRpeVacfXw4cOYMWMGtm7dirS0zB9mODo6olOnThg9ejTq16+fWy+bP8XGSuvEGRMfD2zeDPToYZGUiIjINI8fPwYAtGzZ0qTntWzZEsuWLcOTJ0/MkVbeJ3ddcq5fTmR2gsx/ZwLk/3uU29akmDLylHssZD2//vorAKBFixYoVkxeYR0A7t27h7/++guA9IEvERERZV/Pnj3x6NEjjB8/HnFxcahRowZ27NgBX19fAEBsbCwUCk60SEREti9XeqsxY8agUaNG2LBhA1JTUyGKYqZHSkoK1q1bh4YNG+J///tfbrxs/hUbm3UbpRKIiTF7KkRElD3e3t4AABcXF5Oel9G+SJEiuZ5TvlCtGuDhYbyNRgM0b26ZfIjysa9bfC2r3eCag2XHbF6qudFRqwIElC5UGgHuAbJjti7dGiqF4XtSVQoV2pRpIzseWcfAgQMxaNAgnDx50qTnnTt3DgMHDsTgwfJ/DomIiMiwjz/+GLdu3UJKSgqOHDmiMwgnOjoakZGRBp8bGRmJjRs3mj9JIiKiLOR45Orw4cMxd+5ciP9NR+vp6YlGjRqhXLlycHNzQ3JyMq5du4b9+/cjPj4eoihi5syZePHiBX788cccH0C+JOcDdY1GXjsiIrKK6tWr4969e7hw4YJJz7t48SIAoEaNGmbIKh9wcZGmzo+IeDWV/uuUSmlNc55fIrNrV64dFFBAA+Prn0aERsiPWbYdShcqjdiEWL1T+YoQMSZkjEkjTcPqhWHe8XnG29QNkx2P7JOor88gIiIiIiKifClHI1f37NmDOXPmAABcXV3x/fffIy4uDlu2bMGsWbMwefJkzJo1C5s3b0ZcXBx+/PFHuLm5QRRFzJ07F9HR0blxDPlPUBBQtaq0Jpwhjo5At26Wy4mIiEwyePBgiKKIxYsXIzExUdZzkpKSsGjRIgiCwBE0OTFhAtCpk/S1Uin9P6NPLVMGWLXKKmkR5UdnPjhjdP+GHhtMiqdUKLGtzzYUcS2iM/VvxsjTD+p8gGG1h5kUs0KRClj21jKoFCooBeWr1xKUUClU+L3b7wgqEmRSTLIfGUVVTv1MREREREREGXJUXJ03T7qDW6FQYNu2bRg+fDicnJz0tnV0dERYWBj++OMPKP/7IDOjMEsmEgRg+nRpxI2hi/yxY4FChSybFxERyfbWW2+hR48euHfvHjp06IAHDx4Ybf/gwQN07NgR9+7dQ+/evdGNN9Bkn4MDsGGDtDZ5u3ZAhQpAw4bAggXAqVOAv7+1MyTKN6r4VsGjMY9QpmAZne2+br64FnYNXSt2NTlmUJEgXAq7hJmtZ6Je0XqoWKQi3qrwFnb334257edmq0jWs0pPXPzoIobXG46qPlVR1acq/q/+/+FS2CX0rNLT5HhkPx49egQAKFCggJUzISIiIiIiIluRo2mBDx48CEEQ0KtXLzRp0kTWc5o0aYJevXph2bJlOHToUE5ePn9r2xZYuxYYNgx4/FgacaPRAM7OwLhxwJdfWjtDIiIyIjY2Ft988w3S09Oxfv16lC9fHu+++y5CQ0MzTa2/a9cuLFu2DElJSXjnnXcwadIkxBpZf7t48eIWPBI7pVBIo1czRrASkdUUcS2CayOu5WrMgs4F8UnwJ/gk+JNci1mucDnMbjs71+KR7UtJScGvv/4KAChVqpSVsyEiIiIiIiJbkaPi6uPHjwEALVu2NOl5LVu2xLJly/DkyZOcvDy99RbQsSOwbRtw8yZQuDDQuTNQsKC1MyMioiyULFlSO3pKEAQkJSVh/vz5mD9/vt72oihCEASsW7cO69atMxhXEASkp2deZ5CIiCi/WLp0KZYuXap335dffonvvvvO6PNFUURycjIuX76M5ORkCIKA0NBQM2RKRERERERE9ihHxVVvb2/cu3cPLi4uJj0vo32RIkVy8vIESGurdu1q7SyIiCgbMtZxM/R9Vu2JiIgos5iYGERHR2eaAloURVy4cEF2nIx+18/PD6NHj87VHImIiIiIiMh+5ai4Wr16ddy7d8+kC1QAuHjxIgCgRo0aOXl5IiIiuzVgwABrp0BERJSn6bspSc6NSoIgoECBAihVqhRCQ0MxevRo+Pn5mSNFIiIiIiIiskOCmINhMOvXr8c777yDgIAAXLx4ER4eHlk+JykpCRUrVsT9+/exdu1adOvWLbsvb3GJiYnw9PREQkKCrGPVKy4OOH0aUKmABg2AAgVyntjmzcDJk0BAADB4sBSbiPKENHUaDt05hGepzxBUOAhlvMpYOyVCLvUH+QzPGVHecifxDs49OAcnlROCiwXDxcG0mWzepFarMfPwTJy+fxrlCpfD+CbjoVQqcxTTHH3o0xdPcfzecQBA3YC6KORSKMcx8xtr9QcKhQKCIGDDhg3o3LmzxV43N7APJSIigP1BdvCcERERYJ7+IEdVuLfeegs9evTA6tWr0aFDB6xduxa+vr4G2z948AA9evTAvXv30KdPH7sqrObY48fA8OHAmjWAWi1tc3MDPv4YmDwZcHAwPebSpcBHHwHPn7/a9tFH0uOHH3InbyKyClEUMefYHEzaOwmPnj/Sbm9RqgXmdZiH8oXLWzE7IiLKr+4l3cNHf3yEzVc2Q4R0j6ankydGBY/CF42/gFJhekF0xPYR+PHoj9p4ADBp3yS8XfFtrO2x1uR45uhDk1OTMWrnKESejkSqOhUA4KR0wsAaAzGz9Uy4ObqZHJMsj9PrExERERERUW7I0cjV2NhYpKWl4bPPPsP69evh7u6Od999F6GhoShXrhzc3NyQnJyMa9euYdeuXVi2bBmSkpLw9ttvY+rUqVAZGWFZvHjx7KZlNtmubicmAvXrA1evviqsZhAEoHt3YOVK6Wu5fv8d6NfP8P6BA4ElS+THIyKbMnnvZIyPHp9pu1JQwtPJE8feP4bShUpbITMCePdrdvCcEdm/x88fo86COriTeAdqUfdvWgEChtQaggWdFpgUc8T2EfjhqOGbAjuW74gtvbeYFDO3+9A0dRpa/NoCh24fynTcCkGBhoENEdU/Cg7KbNwsmQ+xPzAdzxkREQHsD7KD54yIiADz9Ac5Kq5mTK2UQRRFne/flNV+bVKCgPT09OymZTbZfgOmTQPGjQM0GsNt9u4FmjSRH7NgQSAhwXibR4+AIkXkxyQim3Av6R6Kzy6e6QPcDCqFCr2r9Mav3X61cGaUgRdopuM5I7J/46LGYfqB6Qb7JwA4NewUavjVkBVPrVbD4WsHnRGr+sT/Lx6eLp6yYpqjD112dhne3fCu0TbL31qO3lV7y46Zn7E/MB3PGRERAewPsoPnjIiIAPP0B4qcBhBFUft48/s3H1ntf7NtnrFggfHCqkoFLF4sP97+/VkXVgFg4kT5MYnIZvx+9nejHzSna9Kx8vxKJKcmWzArMqf4+Hh8++23CA0NRUBAAJydnfXO7rB7924sX74cO3futEKWRJTfLTixwGhhVaVQYckp+TOnzDw8M8vCKgB8tO0j2THN0YcuPLkQCsHwZZNCUGDBSdNG7JL1paWlYf/+/ViwYAGmTp2KSZMmWTslIiIiIiIishM5WnN1wIABuZVH3nbvnvH96elATIz8eGfPymt3/br8mERkM+4k3oFSUEIjGr4pI02ThkfPH3GNtzxg1apVGDZsGJKSkgC8Wg9O30wPZ86cwejRo+Hi4oL79+/zzlsisph0TTqevHhitI1ao8btxNuyY56+f1pWu6tPr8qOaY4+9FbCLaPxNKIGt+Jvyc6RrCs1NRVff/01fvrpJyS8ccPq+PG600mPGTMGmzZtQmBgIKKioiyZJhEREREREdmwHBVXl3BNT3kKFwbu3jW8X6kE/P3lxytVSl67gAD5MYnIZni7ehv9EBeQRsl4uXhZKCMyl19//RWDBg3SFlT9/f3h7u6Of/75R2/7gQMH4rPPPsPLly+xZcsW9O3b15LpElE+phSUcHd0R1JqkuE2CiV83HxkxyzjVUZWu6LuRWXHNEcf6uvmi1vxtwyOiBUgwK+An+x4ZD1PnjxBq1atcObMmUyzJem7qalr166YOXMmrl+/juPHj6NOnTqWSpWIiIiIiIhsWI6nBSYZBg2SCqiGqNVAv37y47VrB7i4ZN3ujTuvicg+9Knax+gHw0pBic5BneHhxFGL9uzevXv44IMPIIoiAgICsHPnTty9exfTpk0z+JxChQqhyX/rc+/evdtSqRIRQRAEDKwxEErB8N+06Zp09Ksm/2/aCU0nyGo3r+M82THN0YcOqjHI6H4RYpZtyDa8/fbbOH36NERRRMOGDfHzzz9nGq36uoYNG6JYsWIAgO3bt1sqTSIiIiIiIrJxLK5awvDhgI+PtLbqm5RKoGlToE0b02JmtZ5qmzZA8eKmxSQim1DGqww+rPshBGQeQaEQFHBUOmJiM66pbO9++uknvHz5Ei4uLoiKikJoaKis59WrVw+iKOLMmTNmzpCISNeYkDHwdPbUW2BVCAp0Kt8JIYEhsuMplUq8XfFto21q+9c2aVSoOfrQftX7oUKRClAJmf+WVwpKVCxSEX2rcSYBW7d+/Xrs27cPgiDg008/xd9//42hQ4eiZs2aRp8XGhoKURRx8OBBC2VKREREREREto7FVUvw8QEOHADq1tXdLghAjx7A1q3GR7bqM2YMMGECoNDzFnboAGzblu10icj6fmj7A8aEjIGT0klne5lCZbB7wG5U861mpcwot+zcuROCIKBPnz4ICgqS/byyZcsCAGJMWaubiCgXBHoG4sDgA5n6IJVChcE1BmN199V6p1Y1Zm2PtehYvqPefbX9a+P4+8dNzjO3+1BXB1fsHbgXoWUy3wTTqkwr7B24F64OribnSZa1fPlyAEC1atUwffp02c+rVk36ebly5YpZ8iIiIiIiIiL7k6M1V18XHx+PhQsX4s8//8TFixfx9OlTpKenIz09Xafd7t27ERcXhyJFiqB169a59fK2r1Qp4OBB4MwZ4NgxwMEBaNkS+G+aqWwJDwfGjgVmzgTOnwf8/IDPPpOKuURk15QKJaa1mobPG32O7de241nqM1QsUhGNijcy+YNrsk03b94EADRq1Mik53l6egIAkpIMr3tIRGQuFYpUwMlhJ3H83nGcun8KTiontC7TOkdrjm7pvQUJLxLw0baPcPXpVRR1L4p5HedlO6Y5+lBvN29s77sdV59cxd+xfwMAGhdvjHKFy2UrHlne0aNHIQgCevfubdLzfH19AQCPHj0yR1pERERERERkh3KluLpq1SoMGzZM+0GvKIoAoPfDizNnzmD06NFwcXHB/fv34eGRz9YMrF5deuQWR0epwEpEeVIhl0LoU7WPtdMgM0hOTgYAFChQwKTnvXjxAgDg7Oyc6zkREclVJ6AO6gTUybV4ni6eWPb2slyLB5inDy1XuBwLqnYqozhaunRpk57n4OAAAEhNTc31nIiIiIiIiMg+5Xha4F9//RV9+vRBYmIiRFGEn58fypcvb7D9wIEDoVKp8PLlS2zZsiWnL09ERGSXChcuDAB48OCBSc+7evUqAMDb2zvXcyIiIsqrMm5KMrVImlGULVSoUK7nRERERERERPYpR8XVe/fu4YMPPoAoiggICMDOnTtx9+5dTJs2zeBzChUqhCZNmgCQpgimHFKrgYkTgU6dgA8+AJ49y3nMZ8+A6dOB0aOB1atzHg8ArlwBvvhCmrb4uOlrZxmMuW4dsH078Px57sQkmxX/Mh5brmzBhksbcCv+lrXTIcqxSpUqAQD27dtn0vO2bNkCQRBQu3Ztc6RFRESUJ/n7+wMALl26ZNLzDh8+DAAoVapUrudERERERERE9ilHxdWffvoJL1++hIuLC6KiohAaGirrefXq1YMoijhz5kxOXp5GjZLWbp0wAdi6Ffj5Z8DdHWjcOHvxNBqgRw/Aw0Mqgs6aBfTsCbi6Ar/+mr2Yjx8DFSsCFSoAU6ZIRdu6daW1Zv8bfWWyq1eBpk2lmO+8A7RvD/j6SkVmjSZ7MclmpaSn4P+2/x/8Zvih88rOeGv1Wyj1fSl0XtEZcc/irJ0eUba1a9cOoihi06ZN2tGoWVm5ciVOnz4NAGjfvr0ZsyMiIspbGjduDFEUsWbNGu0yNll5/Pgx1q1bB0EQ0LRpUzNnSERERERERPYiR8XVnTt3QhAE9OnTB0FBQbKfV7ZsWQBATExMTl4+fxs7Fpg9G9D3wcD+/UB2RjR17AisWZM55osXwIABpo9iTU0FypUDLl/OvO/uXaBqVeDhQ9NixsYCwcHAgQO62589k4rMw4ebFo9smiiK6L6mO+Ycm4MUdcqr7RCx/ep2NFzcEPEv462XIFEODBkyBF5eXkhNTUXnzp1x8+ZNo+1XrVqFoUOHQhAEBAQEoE8frsVLlNdoRA22X92Ofhv6of2y9gj7Iwwn75+0dlqZxCbEYvye8ei4vCPeWf0OIk9H4kXai2zHE0URh+8cxrAtw9B+WXsM3DgQUTeiZBfA9ElTp2HNhTXotbYXOizvgE93foorj69kO565XHl8BZ/u/BQdlndAr7W9sPbiWqSp06ydVp707rvvApCm1//mm2+ybJ+amop3330Xz58/hyAIGDhwoJkzJCIiIiIiInuhysmTMz4IbtSokUnP8/T0BAAkJSXl5OXzt+nTje8/eRK4eROQO33V1avS9LrGhIVJI1vlCg8H4uMN709JAT76CFi7Vn7MiAggIUGaDlmfuXOB//s/wIRiP9mu3Td3Y8s/+tdmThfTERMfg7nH5mJc43EWzowo5zw8PDBv3jz06tUL//zzD6pUqYJu3brByclJ22bOnDm4ffs2duzYgXPnzkEURSiVSixevBgODg5WzJ6IclvCywR0WN4BB24fgFJQQi2qoVKoMPf4XHxY50P81P4nKIQc3ReZKxafWoz3t7wPAFCLaigEBdZdWocvd3+JqP5RCCpi2t9g6Zp0DN40GL+d/Q0qhQrpmnSoBBWWnlmKNmXaYH3P9XB1cDUp5r2kewj9NRSXHl/Snsud13Zi5qGZ+KbFNzbzd8M3+77Bl3u+hEpQIV1Mh1JQYtWFVahYpCKi+kfB393f2inmKY0bN0aHDh3wxx9/IDw8HLdv38aYMWMytXv+/Dn+/PNPTJo0CWfPnoUgCHj33XdRoUIFK2RNREREREREtihHn9AkJycDAAoUKGDS8168kO5sd3Z2zsnL51/Ll8ub/nboUPkxx4/Pus3jx8D58/JjLlmSdZs//pAfLz0dWLpU+r8hKpXUhvKEyDORUCkM3wOiETVYeHKhBTMiyl3du3fH/Pnz4eDggBcvXmDFihWIjIyEIAgAgP/7v//Dt99+qy2sOjo64pdffkGrVq2snDkR5bb+G/vj8B1pbUe1KN1Elq6R/uaZd3weZh2aZbXcMuy7tQ9DNg+BWlRrc9SI0t+kcc/iEPpbKFLSU4yFyGRi9ET8fvZ3AK+ON12U/r/rxi58+MeHJsUTRREdl3fE1SfSdOvac/lfzC92f4GV51eaFNMcVpxbgS/3fAngVW4ZuV59chUdV3TM0chd0u/3339HxYoVIYoifvnlFwQFBenMBOHt7Q1PT0+88847OHv2LERRRPXq1TF37lwrZk1ERERERES2JkfF1cKFCwMAHjx4YNLzMtaW8/b2zsnL51/Hj8trd+eO/Jhy2168KD9mYmLWbVJM+AAuMVGaojgrd+/Kj0k27XbCbe0HrYZw3VWyd0OHDsWxY8fQtWtXCIIAURQzPQBpjdUjR45gwIABVs6YiHLb1SdXsfnKZm1xTZ9vD35r9elipx+YbnD0rFpU407iHay9KH9GkuTUZHx35DuI0F9E1IgaLDu7DPeS7smOuffWXpyKO6UtWL5JAQWm/D3FqoVLURQxZf8UKAxciqWL6Th5/yT+jv3bwpnlfZ6enjh8+DB69uyp7WNfvHihvanpyZMnUKvV2n3du3fHvn374Opq2uhpIiIiIiIiyttyVFytVKkSAGDfvn0mPW/Lli0QBAG1s7MuKAE1ashr5+cnP6a/zGnHypeXH9PdPes2jo6mxZMz2lnusZDNK+peFEpBabSNtytv0iD7V7VqVaxfvx5PnjzB1q1b8dNPP+Hrr7/Gd999h7Vr1yIuLg5bt25F9erVrZ0qEZnBjms7spzy92HyQ5x5cMZCGWWmETXYcW2H0QKwUlDij6vyZyU5fOcwnqU+M9pGLaqx6/ou2TG3Xd1mfNYLaHDu4Tk8SDbt5tDcFPcsDucfnocGhmeiUSlU+OMfE2Z4Idnc3d2xYsUKnDlzBqNGjUKdOnVQuHBhKJVKFCxYEFWqVEFYWBiOHDmCVatWmTxLExEREREREeV9OVpztV27doiKisKmTZtw9epVlCtXLsvnrFy5EqdPn4YgCGjfvn1OXj7/6t8fGDQo66mBFyyQH3PiRGDNGuNtvLzkF3YB4N13gVlZTGHXtq38eA4OQN++xqcGTk+Xzg/lCf2r98fy88sN7lcKSgypNcSCGRGZl6enJ/tGonwoRZ0CAULW7Uyccjc3iaJotLAKSAXYVHWq7Jhy25oaU865NCVmbpPz2gIEq+aYH1StWhUzZsywdhpERERERERkh3I0cnXIkCHw8vJCamoqOnfujJs3bxptv2rVKgwdOhSCICAgIEBnfRsy0fDhxvdXqWLaKNOKFYHmzY23mT1bfjwA+OYb46NXHRwAU9cv+uILoEABQKlnNKMgAO+9B/w3oprsX6syrdCmTBu9o3lUChWKehRFWN0wK2RGRESUe+oE1MmycOmkdEJln8oWyigzpUKJqj5VjRYuBUFAnYA6smNW96ue5YhdACbFrO1fG2ka49Mne7t6I8A9QHbM3FbUoyiKuBYx2iZNk2bScRMRERERERGR5eSouOrh4YF58+YBAP755x9UqVIF7777LjZv3qxtM2fOHHz++eeoUaMG+vTpg+TkZCgUCixevBgODg45yz4/++47YOhQ/ftq1QLOnTM95l9/AR06ZN7u6CgVQU0dEersDFy+DJQsmXmftzdw8iQQYOIHW6VKAQcOSMf45mv973/A/PmmxSObphAU2NBzAwbXHJxpir+mJZriwOADKOxa2ErZEVnGw4cPsXnzZqxfvx7Xr1+3djpEZAZNSzRFUOEgg1PhKwUl+lbri4LOBS2b2BtG1B9hcH1UAQKUghKDaw6WHS/APQBdK3Q1eNwqhQp1A+qipn9N2TG7V+4OL2cvg0VbhaBAWN0wo1MHm5tKoUJY3TCjORZ2KYy3K71t4cyIiIiIiIiISA5BFEX9n5CYYOHChRg+fDhSU1MhCIbvZhdFEY6Ojvj5558xYMCAnL6sxSUmJsLT0xMJCQnw8PCwdjoStRoYPRo4fVoqVH7/vVS4zImnT4GZM4EnT6Qi5pAhgCJHdXipkBoZKeXbvTvQrFnO4gHSMZ8/D7i4AKGhgKdnzmOSzXqY/BDRMdFIU0sjOYKKBFk7JcrHcqM/ePr0KSIjIwEAHTp0QFBQ5p/pyZMn45tvvkFa2qtRWD179sTixYvhLGcNahtik30okQ05++AsmkY2xbOUZ0gXXy1/oBAUqORdCfsG7kMhl0JWzFCa9rfv+r5YeX4lFIICGlFaokKlUEEURSx/ezl6VO5hUswHzx6g4eKGuBl/UxsPkArKXi5eODD4AMoVznrpkdftubkH7Ze3R7omHeka6VxmjLhtWrIpdvTdASeVk0kxc9vL9Jdo+3tb7Lu1DwC0RWuVQgWVQoXtfbejWclmVszQfGylP3jy5Am2bNmCo0eP4t69e0hKSoK7uzsCAgJQv359dOzYEYUL28ZNfLZyzoiIyLrYH5iO54yIiADz9Ae5UlwFgHPnziE8PBybN2+GRs9aoIIgoF27dvjmm29QvXr13HhJi2OHTEREQO70B/PmzUNYWBgcHR1x9+7dTB/gLlu2DP369YMgCHi9qxYEAd27d8fKlStzdAyWxj6UKGuxCbGYfWg2lp5ZioSUBAR6BOKDOh8grG4Y3J2MLLVgQRpRg9/O/IYfjv6AM3Fn4Kh0RJegLhgVPAp1i9bNVsx/X/yLn47+hJ9P/Iz7z+7Dy8ULg2sMxsgGI+Hv7p+tmJceXcLMQzOx+sJqJKclo7xXeYTVC8P7td+Ho9IxWzFzW0p6ChaeXIg5R+fgn6f/wM3BDT0q98Do4NGo6F3R2umZjbX7g6SkJHz22WeIjIxESorhdYydnJwwePBgTJ06FQUKFLBghplZ+5wREZFtYH9gOp4zIiICbLy4miEhIQEHDhxATEwM4uPjUaBAARQrVgyNGzeGd05HVFoZO2QiIgJypz/o0aMH1q5di5YtW2LXrl2Z9pcpU0a7lnmXLl1QqlQprFu3Drdv34YgCIiOjkbjxo1zdByWxD6UiIgA6/YHsbGxaNGiBW7evAk5l8GCIKB06dLYvXs3AgMDLZChfuxDiYgIYH+QHTxnREQEmKc/yPXFhjw9PdG+ffvcDkuGpKVJU+L+8w/g5QWsXw/omVrSJM+fS+uvxscD5coBDRoARqZ7luXePWDfPmla4OBgoHTpnMUzh/R0YM8e4P59wN8faN4cUFlvPS57Fv8yHrMOzULcszhU9akqrSuW06mlifKYf/75B4IgIDg4ONO+gwcP4ubNmxAEAZMnT8a4ceMAAJ9//jkqVqyI+Ph4/Pbbb3ZVXCUiIrKm1NRUtG3bFjdu3AAAFChQAH379kVoaCjKlSsHNzc3JCcn49q1a/jrr7+wbNkyJCUl4fr162jbti1Onz4NBwcHKx8FERERERER2QJWjuxZ/frA0aOvvo+LAypUAAoWBP791/R4ogjMmAF8/TWQmPhqe4UKwC+/AA0bmh4zKQn44ANg5UogY7poQQDatwcWLQJ8fU2PaQ6rVwMjR0qF1Qz+/sDs2UDPnlZLy95oNBr0WtcLay6u0dk+aucoTGkxBWMajrFSZkS25/HjxwCAcuUyryX4119/AZCmJBwxYoR2u4+PD3r37o25c+fi8OHDlkmUiIgoD5g7dy4uX74MQRDQoEEDrFmzBgEBAZnaVatWDW+99Ra++uor9OjRAwcOHMDly5cxd+5cnT6ZiIiIiIiI8i+LDCV7+PAhNm/ejPXr1+P69eu5EnPChAkQBEHnUaFCBaPPWbNmDSpUqABnZ2dUrVoV27Zty5VcrKJpU93C6uvi44HsDG2ePBn43/90C6uANCq2ZUvg+HHT4qWnA+3aAatWvSqsAlIRd8cOoHFjqfhqbWvWSAXU1wurgPR9r17SfpLlrdVvZSqsAkC6Jh3/++t/+PHIj1bIisg2PXnyBADg5uaWad+BAwcAAI0bN860v1q1agCkqQ2JiIhInlWrVgEA/P39sX37dr2F1df5+/tj27Zt2nb2ttY5ERERERERmU+OiqtPnz7FrFmzMGvWLFy5ckVvm8mTJ6N48eLo1q0bunfvjvLly6NPnz54+fJlTl4aAFC5cmXcv39f+9i/f7/BtgcPHkTv3r3x3nvv4dSpU+jatSu6du2K8+fP5zgPq9i3z/j+pCTg77/lx3v0SCqu6qPRSIXSsWPlxwOAjRuBAwekqYDfpFYD165JI2KtSa0GPvnEeJtPPtF/DKTjXuI9bLqyyWibsVEm/gwR5WHCf9Ot//vGTAMajQZHjhyBIAh6p/0tXLgwAOD58+fmT5KIrCL+ZTxi4mPwPM12/50/T32OQ7cP4fwDO/1bmvKdK1euQBAEDB48WPYaO+7u7njvvfcgiqLB610iIiIiIiLKf3JUXF21ahU+/fRTjBs3DkWKFMm0f9myZQgPD0daWhpEUdQ+Vq1ahYEDB+bkpQEAKpUKfn5+2oe+HDJ8//33aNu2LcaMGYOKFSti8uTJqFWrFn766SeDz0lJSUFiYqLOwyZ89pm8dj16yI+5erXu6NI3qdXSOqxvju40JjISUCqNt1m0SH48c9i3D7h713ibu3ezLmYTJu2dlGWb5LRk7Lq+ywLZENk+Hx8fAMDVq1d1th8+fFjb3zRo0CDT8549ewYAcHFxMXOGRGRpx+4eQ/tl7eE1zQulvi8Fr2leeG/ze7iTeMfaqWk9ff4UjRc3RoGIAghZHIKq86vC9RtXjN452tqpERmVmpoKQLpB1xSVKlUCAKSlpeV6TkRERERERGSfclRc3bNnDwBp2sKMkTSvGz9+PABAFEV06dIFI0eORGBgIERRxJo1a/C3KSMr9bh69SoCAgJQunRp9O3b1+gUiYcOHUJoaKjOtjZt2uDQoUMGnxMREQFPT0/tIzAwMEf55ppjx+S1M6UYHBeXdSEUAB4+lB/z7l3jIz5F0bRirTnExeVuu3wsNlHeFKVXnvCufyIAqFmzJkRRxMqVK7Uf+ALAwoULAQCOjo5oqGet6xs3bgBAltMZEpF9iboRhYaLG2Ln9Z0QIQIAUtQp+PXMr6izoA5uxd+ycobSiNqS35fE/tv7tTkCwIv0F5h1aBY6Le9kxeyIjCtWrBgA4MWLFyY9L6N90aJFcz0nIiIiIiIisk85Kq7+888/EAQBwcHBmfYdPHgQN2/ehCAI+Prrr7FhwwbMmjULx44dQ6FChQAAv/32W7Zfu379+oiMjMSOHTswb9483Lx5E40bN0aSgTU84+Li4Ovrq7PN19cXcUaKZmPHjkVCQoL2cfv27Wznm6tCQuS1++88yxIQIE39a4wgAH5+8mMGBhov2AoC8N+HHFYjtzjBD1OyVLJgSVntqvhUMW8iRHaie/fuAIDbt2+jZcuWmD9/PoYOHYqlS5dCEAR07txZ7+jUw4cPQxAEVKxY0dIpE5GZpGvS0W9DP6hFNdSiOtO+Jy+eYNSfo6yU3Sv91vdDUqr+v7UBYOvVrdgXw9k+yDa1atUKoihi9+7dJj0vKioKgiCgdevWZsqMiIiIiIiI7E2OiquPHz8GAJQrVy7Tvr/++gsA4OTkhBEjRmi3+/j4oHfv3hBFEYcPH872a7dr1w7du3dHtWrV0KZNG2zbtg3x8fFYvXp1tmO+ycnJCR4eHjoPm/D11/LabdggP2aPHoCDg+H9SiXQti3wRoHaqMGDs16rdMgQ+fHMoXFjoHhxqdCrjyBI+xs1smxedmhC0wlZtnF3dEezks3MnguRPejduzfq168PURRx8OBBhIWFYfHixQCk/ic8PDzTc+Lj4xEdHQ1AusmIiPKGHdd24P6z+9CI+pdoSNekY+OVjYh7Zt2ZNHZc25Flm3G7x1kgEyLTDR8+HC4uLlixYoXsGZT+/vtvrFy5Eq6urhg+fHi2XzsiIgJ169aFu7s7fHx80LVrV67hSkREREREZMdyVFx98uQJAMDNzS3TvgMHDgCQpgx+c3+1atUAwOg0vqYqWLAgypcvj2vXrund7+fnhwcPHuhse/DgAfxMGYlpS9q2Nb6/YEGgbl358QoXBiZP1r9PqQQcHYGICPnxAKBTJ6B5c0Ch58dMqQQqVZIKsNakUAA//CB9/WaBNeP7H37Qfwykw6eAD3pV7mW0zYzWMyyUDZHtEwQBf/zxB7p27QpBELTrkhctWhTr1q3TrvH2usjISO2ab29OdU9E9uvSo0tQCsaXZ9CIGlx7qv/vXEt4mf4S6WIWs5wAuBl/0wLZEJmufPnyWLJkCVQqFdq3b4+5c+fqTMv/urS0NMybNw8dOnSAg4MDlixZoveGYrn27t2LsLAwHD58GLt27UJaWhpat26N5OTkbMckIiIiIiIi61Hl5MnCf8Wnf//9V2e7RqPBkSNHIAgCGjdunOl5GeuzPn/+PCcvr+PZs2e4fv06+vXrp3d/cHAwoqKiMHLkSO22Xbt26Z3S2C5s3w60aAH8t+6tDh8f4I1CsixjxgBubkB4OPBf4RwAUK0asGABUL26afGUSmDrVmDkSCAyEvivIACFAujWDZg/X3o9a+vSBdi4ERgxAoiJebW9RAng+++Bzp2tlZndWfHOCrg4uGDp6aXQ4NXoGyelE2a1mYX3a79vxeyIbI+XlxfWr1+PR48e4caNG3Bzc0OlSpWgMHBDR6VKlbBkyRIIgoDatWtbOFsiMhd3J3eDo1Z12jm6WyAb/RwVjrLaOauczZwJUfZMmjQJgDQ98NatWzF8+HB89dVXaNSoEcqVKwc3NzckJyfj2rVr+PvvvxEfHw8A6NixIy5evKh9vj7jx483+to7duiO+o6MjISPjw9OnDiBJk2a5OzAiIiIiIiIyOJyVFz18fHB7du3cfXqVZ3thw8fRmJiIgRBQIMGDTI979mzZwCgdy05uT799FN06tQJJUqUwL179xAeHg6lUonevXsDAPr374+iRYsi4r/RliNGjEDTpk0xc+ZMdOjQAStXrsTx48exYMGCbOdgdbt3SwXL3r2BkycBf39g0yagSJHsxRMEICwMGDoU2LcPSEgAypY1vaj6OldXqTAbEQEcOABoNNKIWltbw7RzZ6BjR+DQIeD+felcBgdzxGo2LO6yGHM7zMXcY3NxN+kuavrWRJ+qfQwWi4gI8Pb2hre3d5btuN4bUd7UOagzwraFQRRFg21KFSyFqr5VLZiVLoVCgZKeJRGTEGO0XZ8qfSyTEJGJJkyYoL05+PWbhLdu3ZqprSiK2jZbt27V2+Z1WRVX35SQkABAuslKn5SUFKSkpGi/T0xMNCk+ERERERERmVeOiqs1a9ZEbGwsVq5ciUmTJsHRUbqjfeHChQAAR0dHNGzYMNPzbty4AQAICAjI9mvfuXMHvXv3xpMnT+Dt7Y1GjRrh8OHD2g+nY2NjdYo5ISEhWL58Ob788kuMGzcO5cqVw8aNG1GlSpVs52ATHByAtWtzN6ajI5Db000WLmz7I0AVCkDPzyuZzlnljFHBo6ydBhERkV0IcA/A0FpDseDEAojQX2Cd2GwiFIJ1b1T6tvW36L6mu8H9zipnfNXkKwtmRGQafTcwGLqpwdjNDq8T3lxaJAsajQYjR45Ew4YNDV6LRkREYOLEiSbFJSIiIiIiIsvJUXG1e/fu2LRpE27fvo2WLVuib9++OHHiBJYuXQpBENC5c2e9o1MPHz4MQRBQsWLFbL/2ypUrje6Pjo7Wm2/37oY/ECIiIiIisoYf2v2AlPQURJ6JhFJQQiEooBbVUAgKTA+djn7V9S99YUnvVHoHES0jMC5qXKYisJuDG44MOQJHlbzpg4ksbY++5VSsICwsDOfPn8f+/fsNthk7dixGjXp1o2JiYiICAwMtkR4RERERERHJIIhyb8nVQxRFhISEaNdXfX27s7Mzjh8/jkqVKuk8Jz4+Hr6+vkhPT8eUKVPw2WefZT97C0tMTISnpycSEhLg4eGRvSCrVwN//CGNOB02TJoiNydSU4FvvwUuXgR8fYHPP5fWXCWyouTUZGy7ug1PXzxFyYIlEVo6FEqF0tppEeWaXOkP8hmeMyJ5rjy+gpXnV+LJiycoVbAU3q32Lrzdsp423JKePn+Kz/76DMfvH4ejwhEDagzAB7U/4BIAJEt+7g8+/vhjbNq0Cfv27UOpUqVkPy8/nzMiInqF/YHpeM6IiAgwT3+Qo5GrgiDgjz/+wJAhQ7B582ZoNBoAQNGiRbFgwYJMhVUAiIyMRFpaGgRBQGhuTz1ry/btAzp0AP5bbxYAsGgRUKIEcPgw4OdnesyJE4FJk6R1TDPMni29zubNXC+ULE4URcw8NBMToicgOS1Zuz3APQALOi5Ah/IdrJgdERGR7QsqEoTwZuHWTsMoL1cvLOy80NppENkNURQxfPhwbNiwAdHR0SYVVm1WSgqwZQsQEwN4eQFdu0r/tzUXLgBRUYBaDYSEAPXqASZO5UxERERERPSmHBVXAcDLywvr16/Ho0ePcOPGDbi5uaFSpUoG71yvVKkSlixZAkEQULt27Zy+vH24cAFo3ly3CJrh1i2gQgXg4UNprVO5vv0WmDBB/74//gDatwd27MhWukTZNe3ANIyNGptp+/2k++i8sjP+fPdPhJbORzdVEBEREVG+FxYWhuXLl2PTpk1wd3dHXFwcAMDT01PvMjo2b80aaRamf/8FlErpOvfDD4HPPpOuUW3hJt+HD4E+faTCakY+Gg1Qq5aUf+nS1s2PiIiIiIjsWo6mBc5vsj10uHFjwMiaOgCki9BwE0YpuLoCL14Yb3PrFlC8uPyYRDmQ8DIBfjP98DL9pd79CihQw78GTrx/wsKZEeU+Ti1kOp4zIiIC8md/IBgYKblkyRIMHDgwy+fb1Dn74w+gUyfpa30fJXz1lTS7kjW9fCktv3P5MpCerrtPpZKW0Tl7Fihc2Dr5ERFlk031B3aC54yIiADz9Ac2cEtpPnDwYNZtFi+WH2/79qwLq4D1L2opX9lweQNS0lMM7tdAg5P3T+LK4ysWzIqIiIiIyLpEUdT7kFNYtSmiKI1Ozfhan2nTgKdPLZeTPqtXA+fPZy6sAtK2uDjg558tnxcREREREeUZOZ4WmGTQNx3wmxIS5Me7eVNeu3v35MckyqGHyQ+hEBRQi+os2wUVCbJQVkRERPmbRqPB/BPzsfzccqRr0tG4eGNMbDYRro6u1k5Nx6PkR1h+bjnuJN6Bt5s3elfpjUDPQGunpUMjarDz+k7su7UPANC0RFO0KtMKCoH3q1I+cfmytOSNMampwIYNwHvvWSYnfZYtk6YCNnQdrtEAS5cC48ZZNi8iIiIiIsozWFy1BJVK/12zrytSRH68atXktStTRn5MohwK9AjMsrAKwOY+KCUiIsqrTt4/icZLGuN52nPttiN3j2DW4VlY0HEB3qtlxeLHa6YfmI4vdn8BjaiBUlBCLaoxNmosPmnwCaa3mm4Txcsrj6+g04pOuPr0KlQK6RIqYn8EynmVw5beW3jjGOUPT55k3UaplNfOnB4+zPoG58ePLZMLERERERHlSdb/pCI/CA3Nus2IEfLjNWoEeHpm3c6UNVyJcqhLhS7wcDI8X7lSUKJpiaYoWbCk5ZIiIr0iIiJQt25duLu7w8fHB127dsWVK8an7I6MjIQgCDoPZ2dnC2VMRKZ6lvoMwYuCdQqrGTSiBkO2DEF0TLTlE3vDz8d/xmd/fYZ0TTo0ogZpmjRoRA00ogYzD81E+B7r/z379MVTNI1sihv/3gAApGvSka6Rbpy88e8NNFvaDE9fWHkaVCJLKFEi6zZqNVCypNlTMapsWekGZ0MUCqB0acvlQ0REREREeQ6Lq5awcCHg6Gh4f7FiQFiYaTF/+sn4/oEDTRsNS5RDrg6umN1mtt59SkEJB6UDZraeaeGsiEifvXv3IiwsDIcPH8auXbuQlpaG1q1bIzk52ejzPDw8cP/+fe3j1q1bFsqYiEz12V+fIVWdarTNyB0jLZOMAWnqNIyPHm+0zYxDM5Dw0oTlM8zgl5O/4NHzR3pn6FCLajxMfojFpxZbITMiCwsMlG4cVir17xcEoFAhoHNny+b1piFDjM8cpdEAw4ZZLh8iIiIiIspzWFy1hGLFgLNngeLFM+9r0AC4ckW6e9YU774LREYCbm6625VKYPhwYMmSbKdLlF2Daw7GirdXoISn7l3ttf1rY9/AfagdUNtKmRHR63bs2IGBAweicuXKqF69OiIjIxEbG4sTJ04YfZ4gCPDz89M+fH19DbZNSUlBYmKizoOILGf9xfVZtjn74KwFMjHs8J3DeJj80Gibl+kvsf3adgtlpN+KcyugEQ1PMaoRNVh+brkFMyKyotmzAReXzAVWQZD+P3cuYO2ZLVq3Bt5551VOr1MqgYYNgX79LJ8XERERERHlGVxz1VKCgoBbt6Qi6+bNgJMTMGAA4OOT/ZgDBkiPzZuBkyelIu7AgcanQCIys15VeqFH5R44evconjx/glKFSqGSdyVrp0VERiQkSKPCvLy8jLZ79uwZSpQoAY1Gg1q1amHKlCmoXLmy3rYRERGYOHFirudKRPK8TH+ZZRsRogUyMSwpNUlWu8QU696ckZCS9chZa4+uJbKYKlWAQ4eATz4B/vrr1faKFYGpU4FOnayXWwZBAJYvByZPBn74Afjv7xy4uEijWiMipOtxIiIiIiKibGIVztKqVZMeualzZ+tPvUT0GoWgQINiDaydBhHJoNFoMHLkSDRs2BBVqlQx2C4oKAiLFy9GtWrVkJCQgBkzZiAkJAQXLlxAsWLFMrUfO3YsRo0apf0+MTERgYGBZjkGIsqsqEdRxD+KN9rGSWnd4kI5r3Ky2pUvXN7MmRhXybsSYhNi9U4LDEjLH/BGMspXqlQBdu0CYmOBmBigcGGgUiX9I0WtxcEBmDQJGDcOOH1amgq4alXA3d3amRERERERUR7A4ioREVE+FhYWhvPnz2P//v1G2wUHByM4OFj7fUhICCpWrIiff/4ZkydPztTeyckJThwVQmQ1XzX5Cr3W9TLa5q2Kb1koG/3KFS6HJiWa4EDsAb2FS4WgQMmCJdG0RFMrZPfKB3U+wB9X/zC4Xy2q8UGdDyyYEZGNKF5c/9I3tsTZWVqKh4iIiIiIKBdxzVVLEkVpCqUffpDWorl2Lecxnz4FunWT7sJt2lSadjinnjyR1mydPRvYuhVIT895TCIisjkff/wxtm7dij179ugdfWqMg4MDatasiWu50ZcRUa7rWaUn6gXUM7i/oHNBLOi0wIIZ6TevwzwUcCwApaC7fqNSUMJB4YDILpEQrDwarn259uhdpTcEZM5DgIA+Vfqgfbn2VsiMiIiIiIiIiKyBxVVLuXIFqFkTCAmR1qf5+GOgXDmgSxcgPj57Mbt2laZg2rgROH8e2LcPqF4dKFUKUOuftswotRr4/HPA3x8YPBj49FNpzZzAQGD79uzlSERENkcURXz88cfYsGEDdu/ejVKlSpkcQ61W49y5c/D39zdDhkSUGw69dwgDqg+Ag8JBu02AgEaBjXBzxE0UcCxgxewklbwr4ejQo3i74tvaAqsAAa3LtMaBwQfQuERjK2cojaD9rdtvmN5qOgLcA7TbA9wDML3VdPza7VerF4CJiIiIiIiIyHIEURRFaydhLxITE+Hp6YmEhAR4eHjIf+L9+1LR8+nTzEVPpRKoVw/4+2/pa7n69QN+/93w/pIlgZs35ccDpGLqrFnSCNvXCQKgUAC7dwNNmpgWk4goD8p2f2AjPvroIyxfvhybNm1CUFCQdrunpydcXFwAAP3790fRokUREREBAJg0aRIaNGiAsmXLIj4+Ht9++y02btyIEydOoFKlrNcatPdzRmTPNBoNDt05hJfpL1G/WH2bKKrqE/8yHg+ePUBh18Io4lrE2unopdaocSvhFgCghGcJKBUm/P1OANgfZAfPGRERAewPsoPnjIiIAPP0B1xz1RJ+/FF/YRWQth06BPzxB9C5s7x4ajWwbJnxNjExwOnTQI0a8mLeuydNA6yv1i6K0uPLL6XRsUREZNfmzZsHAGjWrJnO9iVLlmDgwIEAgNjYWCgUrya4+PfffzF06FDExcWhUKFCqF27Ng4ePCirsEpE1qVQKNCweENrp5Glgs4FUdC5oLXTMEqpUKJ0odLWToOIiIiIiIiIrIjFVUtYutT4NL1KpVQslVtc/eUX/UXQN338MbB/v7yYa9YY36/RSKNr79wBTFyXj4iIbIucSSuio6N1vp89ezZmz55tpoyIiIiIiIiIiIiI7AOLq5bw9Knx/Wo18OCB/HhXrshr9/ix/JiPH0tFXo3GeLsnT1hcJSIiIiIiys80GiA6WpoxycsLaNMG+G9pgWxLTgb+/BOIjwfKlQMaNZKWqMmJ27eBvXula+7gYKB8+ZzFE0XgxAng3DnA1RVo3RooVChnMYmIiIiIyO6wuGoJgYHA1auG96tUQJky8uM1bixN4ZsVU2KWKAGkpxtvo1AARYvKj0lERERERER5y86dwPvvA7duvdrm6QlMnAj83/+ZXhAVRWDqVOCbb6QCa4ayZYFFi4AmTUzPMTERGDpUmqHp9Rk7WrcGIiMBf3/TY547B/TvLy2/k8HJCfjoI2DaNMDBwfSYRERERERklxRZN6EcGzZMKkwakp4ODB4sP163blJBNiuLFsmP2aMH4OxseL9SCXTtChQpIj8mEREREcl2/N5x1F9YH8pJSggTBThOdkTXlV3x8NnDbMc8evcoeq/tDY8ID7hNcUOzyGZYf2m9rOnBiYgyiY4G2rcHYmN1tyckACNHAjNnmh5zwgRg3DjdwioA3LgBtGoFHD1qWry0NGkk7bp1mZfT2b1bulk5MdG0mNevS887d053e0oK8N13UrGZiIhkmTNnDkqWLAlnZ2fUr18fR438nl+4cCEaN26MQoUKoVChQggNDTXanoiIyFJYXLWEDz4AqlSRCpRvEgTp7teQENNiTp1qfH/LloCfn/x4Hh6GR8MqlYC7OxARIT8eEREREcm2+cpm1FtYD0fvHYVGlJZpSNOkYdOVTSj5fUnEJsRmESGz3878hga/NMDaS2uRlJqE52nPsT92P95e/TZG7BjBAisRmW7MGKlgaej3x/jxphUuHz4EpkzRv0+jkabz/eIL03LcsAE4fFh67pvS06Wi7S+/mBYzY1StvpiiKI2GPX/etJhERPnQqlWrMGrUKISHh+PkyZOoXr062rRpg4cP9d9MGB0djd69e2PPnj04dOgQAgMD0bp1a9y9e9fCmRMREelicdUS3NykdV769wccHV9tL1hQukt38WLTp04aPRqYMUN/wfatt4C//jI9z2HDgOXLgVKldLe3bAkcOpTz9WmIiIiIKBONRoPua7pDhP5ixYv0F2jzexuTYsYmxGLQpkEQISJd82rpB7UoFQZ+PPojNl7emO2ciSgfunoVOH5cKnoa8uKFVNyUa/Vq4/HUauna9v59+TGXLtV/nfw6U2Z5SkuTrpONLaOjUgG//SY/JhFRPjVr1iwMHToUgwYNQqVKlTB//ny4urpi8eLFetsvW7YMH330EWrUqIEKFSrgl19+gUajQVRUlIUzJyIi0sXiqqUULCgVUe/flwqtBw8CcXHSnb1ZXfgZMnq0dIG3ciXw4YdSsTU9XZr+KLt69wauXQNOngT27JHW0fnzT6BChezHJCIiIiKD5h6fi1R1qtE2lx9fNmn06s/Hfza6Xyko8f2R72XHIyLCgwdZt1Eq5bV7Paac62EDI5r0undP/wjTDKIoXYvLlZQkTf+bFVNiEhHlQ6mpqThx4gRCQ0O12xQKBUJDQ3Ho0CFZMZ4/f460tDR4eXnp3Z+SkoLExESdBxERkTnIWLiTcpWXF9CkSe7G7NlTeuQWhQKoWTP34hERERGRQX9e+1NWu+1Xt2NYnWGy2h65e0Q7SlUftajGsXvHZMUiIgIAFC2adRu1GihWzLSYxkaEAtIsT/7+8mMWLy6tjWqowCoIQGCg/HgeHoCLizQq1xhTjpuIKB96/Pgx1Go1fH19dbb7+vri8uXLsmJ89tlnCAgI0CnQvi4iIgITJ07Mca5ERERZ4chVIiIiIiIrclQ6Zt0IgLPKWXZMB6UDBBhfdkKl4H2WRGSCUqWAhg2NjzQtUADo0kV+zB49AAcHw/uVSqB9e8DHR37MwYONj1wFgKFD5cdTqYCBA6X/G5KeLrUhIiKzmTp1KlauXIkNGzbA2Vn/38Vjx45FQkKC9nH79m0LZ0lERPkFi6v27ulTICwMaN0a6NMHuHTJ2hkRERERkQmG1BqSZRsBAt6u9LbsmO3KtjO6X6VQoUO5DrLjEREBAGbNkoqMCgMfJcycCbi5yY/n5QVMmaJ/n1IJODkBERGm5dixIxAaqj9HpRKoUsX0Qui4cUChQoYLy8OHA+XKmRaTiCifKVKkCJRKJR68MX38gwcP4OfnZ/S5M2bMwNSpU7Fz505Uq1bNYDsnJyd4eHjoPIiIiMyBxVV7FhYGFC4MzJ0L7NoFrFgBVKoEBAdnPbUSEREREdmEduXawdvV2//fNZ8AAEJuSURBVGibVqVboYBjAdkxB1QfgELOhaAU9BcCNKIGnzT4xKQ8iYhQrx6wcWPmIqMgAF98Abz/vukxR48G5s/PPDq1Vi1g/36galXT4imVwObN0tI5b+YZGgrs3WtaARiQpvw9fBho2lR3u6cn8PXXwHffmRYvQ0oKEBkpLR1UurT0/8hIeWu8EhHZGUdHR9SuXRtRUVHabRqNBlFRUQgODjb4vOnTp2Py5MnYsWMH6tSpY4lUiYiIssTiqr0aN04qqupz+HDur+tKRERERGZzZMgRuDno/7C/nFc5/NH3D5PieTp74s9+f8LTyRPCf/8BgFJQQikosbTrUtQtWjfHeRNRPnP9OtCuHZCWprtdFIFvvpFGtmbHsGHAnTvAnj1S8fbcOeDoUaBmzezF27EDWLNGd5tSCezcCaxcmb2YpUsDUVHAtWvApk1SrPv3paKyoZG8xsTHA40aAYMGAQcOADdvSv8fNEiafjk+Pnt5EhHZsFGjRmHhwoVYunQpLl26hA8//BDJyckYNGgQAKB///4YO3astv20adPw1VdfYfHixShZsiTi4uIQFxeHZ8+eWesQiIiIAACCKIqitZOwF4mJifD09ERCQoJ1p5XQaAAXFyA11Xi7y5eBoCDL5ERElI/YTH9gR3jOiLL2Mv0lJu2dhN/O/Iak1CT4FfDDpyGfYnCNwVBk54N7AAkvE/Db2d+w7eo2pKpT0aBYA7xf+30U9yyey9kTycP+wHQ2dc4cHTMXVt9k7Y8Ybt2SpuhNT9efiyBINyTXq2f53F7Xu7dUANa3PqxSCXTvLs1ORUT0H5vqD3Lgp59+wrfffou4uDjUqFEDP/zwA+rXrw8AaNasGUqWLInIyEgAQMmSJXHr1q1MMcLDwzFhwoQsXyuvnDMiIsoZc/QHLK6awGY65E2bgK5ds27Xvz+wdKnZ0yEiym9spj+wIzxnREQEsD/IDps5Z6dPyxtJ+s47mUeNWtLYscC33+ovWgLSmrE9egDLllk2r9fduwcEBko3ThuiUAC3bwMBAZbLi4hsms30B3aE54yIiADz9AecFtge3b0rr92jR+bNg4iIiIiIiPKHL76Q1+7PP82bR1Z27zZcWAWkEa2vrfdnFQcPGi+sAtL+gwctkw8REREREZmExVV7VFfm+lgVK5o3DyIiIiIiIsofsioG2gp7mJzLHnIkIiIiIiKDWFy1R3XrAoULG28jCEB4uGXyISIiIiIiorwtIkJeuzZtzJtHVlq2lNYsNUSlAlq0sFw++oSESNP+GqNQSO2IiIiIiMjmsLhqr/5b2N2gTz4BuJYAERGRZSUnAxs3Sv30gQMcmUIme5n+EpuvbEbk6UhEx0RDI9rJSLEcSk1PxfQD0zFk8xBM2DMBz1KfWTslInpTjRqAg0PW7ay53ioADBsmFSYFQf9+tRoYMcKyOb2paFFp3VdDRWClUtrP9VaJiIiIiGySytoJUDZ17Ahs2QIMHqy7tqqLCzBuHPDll9bLjYiIKL8RRWD6dODrr4FnrxWFypUDFi8GGjWyXm5kF0RRxE9Hf8JXe75CQkqCdnvJgiWxoOMCtCrTyorZmdcXu7/A1P1TdQrJk/ZNwoAaA7CkyxIrZkaUhxw/DmzeDDg6AgMHAsWKZS/OpUtA2bKG98+cmb24gLQW6oEDQHy89BqVK2cvTsmSwMqVQM+e0lTGGdMZKxRSf/3TT0D9+tnPM7fMmwdcvQqcOCHlptG8+n/16tJ+IiIiIiKySRy5as86dgQePpQuxhYuBHbuBJ4/Z2GViIjI0iZNAj7/XLewCgDXr0vTEx47Zp28yG7MPjwb/7fj/3QKqwAQmxCL9svbY2/MXitlZl4T9kzAlL+nZBqhK0JE5OlIDNgwwEqZEeURFy5IhdS6dYHJk4GvvgICA4E6dTL3WXKUKQMEBenf5+QEjBqVvTwXLJBGczZrBnTtClSpAjRoAJw+nb149esDbm6668RqNFKOtjLVbsGCwP79wJIlUk4lSwLBwdJNWQcOSPuJiIiIiMgmCaLI+erkSkxMhKenJxISEuDBKXeJiPIt9gemy9Pn7OFD6QPh9HT9+5VKoHlzYNcuy+ZFdiMxJRF+M/zwIv2F3v0KQYHa/rVxdOhRC2dmXhqNBs7fOCNNk2awjQAB8Z/Fw8M5j/3eyMfydH9gJtk+Z7Gx0gjQNAP/xgICgNu3s17783U1axoveDo6Aikp8uMBwKxZwOjRmbcrlVIx9MgRqdgq14sXgKen4eMWBCAmBihe3LQ8iYisjH2o6XjOiIgIME9/wJGrRERERDmxerXuyJg3qdXAX38B9+9bLieyKxsvbzRYWAUAjajBsXvHcPXJVQtmZX6/n/vdaGEVkEawTj0w1UIZEeUxQ4caLjACwL17wA8/mBYzq5GkqanAn3/Kj/fvv8DYsfr3qdVSofbzz+XHA4D+/Y0ftyhKo2OJiIiIiIiyicVVe3fpkjSFUGCgdDfv1q05jxkTA8yYIU0vvHQpkJyc85hERER51YMH0uiarDx8aP5cyC7FPYuDUsj6ZyjuWZwFsrGcG09vyGp3K/6WmTMhyqN27866zY8/yo83cKC8dm+/LT/mqlXGC6FqNbBtm2l96ObNWbfJ7nTDREREREREAFTWToByoGFD4ODBV9/fuQN06gQULixN7+TiYlq81FTgo4+kNV4EQfqgOC0N+PhjaQ2c3r1zN38iIqK8wNiUwBkEAfDzs0w+ZHeKeRSDWlRn2a6oR1ELZGM5Fb0rympXxquMmTMhyqOy6psA4MkT+fFev/Y05oXhkfiZ3L0LqFRZjzS9fx/w8ZEX01is12MSERERERFlE0eu2qtOnQxf3D55ApQoYXrMsDCpsCqK0vSGGRelz54BffsCO3ZkP18iIqK8qkcPwMHB8H6lEmjXDvD1tVxOZFe6BHVBAccCBvcrBAUaBTZC6UKlLZiV+XWv1B1OSiejbQQI+LyhiVOCEpFEzqwKnp7y41WrJq+do6P8mL6+0ujUrMgtrAJSsZaIiIiIiMiMWFy1R2p11tP/PnoE7NsnP2ZMDLBokeE7eAUBGD9efjwiIqL8wssL+OYb/fuUSsDJCYiIsGxOZFfcHN0wo9UMvfsUggIqhQozWuvfb88UCgW+aWHg385/wuqGwdXR1UIZEeUxDRtm3WboUPnx1q6V127pUvkxe/QAFEY+llAqgZYtAX9/+TFbtcq6TUV5I+eJiIiIiIj0YXHVHsldF2fMGPkx162TCqiGaDTAsWPALa55RURElMmnnwLz5gHe3rrba9UC/v5b/mgfyreG1RmGyC6R8C+gW0Co4lMFewbsQf1i9a2UmXmNDhmN6aHT4ajUHemmFJT4pMEn+LG9CetBEpGuBQuMFy4LFQI+N3FkeMmSxvcrFFLBVC4fH2DsWMOxlEpgyhT58QBg+XLjxw0Aq1ebFpOIiIiIiOg1nC/HHsXGymuXmCg/Zny8dOGq0Rhvl5AgPyYREVF+8sEHwHvvScXUhASgbFmgalVrZ0V2ZECNAehbrS8OxB7AkxdPUKpgKdTwqwHB2A1wecCYhmMwOng0fjv7Gy48uoCSBUvi/drvQ6XgpQpRjgQFSbMZtW4NPH+uu69YMeDECdOn0L15U5rK9+HDzPsEIfPryDFxorQkzfTputej7u7Ahg1AvXqmxfP0BM6ckZ735vqvKhWwbRtQpYrpeRIREREREf2Hn1jYozZtgNmzs25XoYL8mOXKvVpj1RCVCggMlB+TiIgov3FwAFq0sHYWZMdUChWalmxq7TQsTqFQYECNAdZOgyjvWbBAf8Hzzh2pcDlsmGnxYmL0F1YBaYmZadNMX05m505g6tTM2xMSgG7dpNczZR1XQCqePn8uHeOPP0pL6/TvL90ERURERERElEOcFtgetWkj7+IyMlJ+zHfeke4MNjQyQqWSpncqVEh+TCIiIiIiIrKOBQuAX381vP+DD4Dr102LWbq08f3h4abFU6uB9u0N709IAGrXNi3m67p1A3bvBvbuZWGViIiIiIhyDYur9urnn43v79FDmg5JLldX6eIbyLw+jUoFFC4MRESYliMRERERERFZx6RJWbcZNUp+vKNHpdGpWQkJkR/zyy+zXprm/PnM0/sSERERERFZEYur9mrgQOC33wBnZ93tCgUQFgasWmV6zF69pPVnXr8zOGPE6rFjQPHiOUqZiIiIiIiILOTu3azbHDwoP17fvvLaHT4sP6bc61ZjI3CJiIiIiIgsjGuu2rN335UeR48Cf/8NBAUBHTvmLGbbttIjNlaagqlYMU4FTERERGQBL9NfYvWF1fjt7G94lPwIZb3KYmitoWhdpjUEQ0s3kMXExMdg/vH52H1zNwCgZamW+KDOByhRsISVMyPKAbVaftu0tNx//axGrWbgyFUiIiIiIrIhLK7mBfXqSY/cxFGqRERERBbzMPkhmi9tjouPLkIhKKARNbjw6ALWXVqH7pW6Y/nby6FS8E93a1l/aT16re0FjaiBWpSKUSfvn8TMQzOx6p1V6Faxm5UzJNKjUCHg33+Nt6laVX68KVPkjV4NDJQfs2lTeaNS5Y6aJSIiIiIisgBOC0xEREREZGW91/bGP0/+AQBoRGkkV7omHQCw9uJaTN472Wq55Xf/PPkHPdf2RLomXVtYBQC1qEa6Jh091vbA1SdXrZghkQEff5x1mxkz5Mfr00deuytX5MdcuDDrNkWLAt7e8mMSERERERGZGYurlNnly8DkycDo0cC8eUB8vLUzIiIiIsqzzj04h90xu7XF1DeJEPH9ke/xMv2lhTMjAJh7bC4gSu/Dm0Rph9SGyNZMmgTUr294/yefAHXrmhZzzRrj+1u3Bpyd5cdzdARmzjS8X6UCjh+XH+9NL19Ky+gcOgQ8e5b9OERERERERK9hcZVeeflSuhu5YkVg4kTgxx+BsDDA3x9YssTa2RERERHlSVE3o6AQjP9ZnpCSgDNxZyyUEb1ux7UdSBf1F74BIF1Mx/Zr2y2YEZEJDh+WbpwtUgQQBOlRrhywahUwa5bp8d55x/AUvcWKAX/+aXrMUaOAbnqm1lapgNWrAT8/02OmpwPh4dJz69cHQkIAHx9gxAjg+XPT4xEREREREb0mTxRXp06dCkEQMHLkSINtIiMjIQiCzsPZlDtq84OhQ6WLbABQq4G0NEAUpaLr4MHA5s3WzY+IiIgoD8qYBjgrr09JS5aj1mR93uW0IbKaL78EHj0CNBrp8c8/QI8e2Yv12WfAsmX69925A9SoYXrMgQOBDRsyb09PB95+G4iKMi2eKEoF4MmTgYSEV9tfvADmzJFG16akmJ4nERERERHRf+y+uHrs2DH8/PPPqFatWpZtPTw8cP/+fe3j1q1bFsjQTly/Dvz+u3SxrY9CId35S0RERES5KiQwJMsCq6uDK6r5Zv33LuW+JiWbQKVQGdyvUqjQrFQzi+VDZFXTpxvff+aMVGSV6949YOlSw/tFERgwQH48ANi1SxrxKmaeyhtqNXDggHTtS0RERERElE12XVx99uwZ+vbti4ULF6JQoUJZthcEAX5+ftqHr6+v0fYpKSlITEzUeeRZ69cDSqXh/RoNcPo0cPOmxVIiIiIiyg/qF62Pmn41DRbwlIISQ2oOQQHHAhbOjADg47ofGx2Zqtao8XHdjy2YEZGVLFokr12XLvJjjhuXdZu7d4GrV+XHXLhQmlLYEIUCmD9ffjwiIiIiIqI32HVxNSwsDB06dEBoaKis9s+ePUOJEiUQGBiILl264MKFC0bbR0REwNPTU/sIDAzMjbRtU1KSdJEppx0RERER5RpBELCm+xr4uPnorL2q+O9P9eDAYESERlgrvXyvpn9NzGk/BwIEnQK4SqGCAAFzO8xFdb/qVsyQyEJ27pTXLjZWfszr1+W1O3VKfsxr16QphQ3RaIAbN+THIyIiIiIieoPdFldXrlyJkydPIiJC3gdNQUFBWLx4MTZt2oTff/8dGo0GISEhuGNkyqKxY8ciISFB+7h9+3ZupW97goKkNVaNcXAAihe3TD5ERERE+UgZrzI4+8FZTG4+GeULl0dhl8KoHVAbv3T6BVH9o+Dq4GrtFPO1D+t+iMNDDqNH5R7wK+AHvwJ+6Fm5Jw4POYwP6nxg7fSILKNsWXntPD3lxyxcWF67EiXkx/T2zvrG4SJF5McjIiIiIiJ6g5G5cmzX7du3MWLECOzatQvOzs6ynhMcHIzg4GDt9yEhIahYsSJ+/vlnTJ48We9znJyc4OTklCs527y33pIughMT9a9No1IBffoABQtaPDUiIiKi/KCwa2GMazwO4xrLmCaTLK5e0XpY9tYya6dBZD0TJwJTpmTdbt48+TG/+ALYtMl4G3d3oH59+THffVdad9UQhQLo319+PCIiIiIiojfY5cjVEydO4OHDh6hVqxZUKhVUKhX27t2LH374ASqVCmq14TWRMjg4OKBmzZq4du2aBTK2Ay4uwJIlgCBkvstXpQL8/ACZo4SJiIiIiIgoj1GpgMaNjbfx8ABatZIfs25doHoW02pPmiQ/HgD06AFUrqx/3dWMa9sPOOKciIiIiIiyzy6Lqy1btsS5c+dw+vRp7aNOnTro27cvTp8+DaVSmWUMtVqNc+fOwd/f3wIZ24lu3YCoKKBRo1fbnJ2BQYOAo0cBnisiIiIiIqL8a98+w8VQDw/gwQPTYx49CtSunXm7IABffgmMHGlaPGdnYPduoEkT6XuF4tUNxFWrSscgdzpiIiIiIiIiPexyWmB3d3dUqVJFZ5ubmxsKFy6s3d6/f38ULVpUuybrpEmT0KBBA5QtWxbx8fH49ttvcevWLQwZMsTi+du0Zs2AvXuBhw+lKYL9/QE3N2tnRURERERERNam0ehfRgaQiqGPHwPFipkW09EROH4cuHBBmi3p33+BKlWA8HDANZvrTfv4SDcOnzsn/V+jAUJCpOmFBSF7MYmIiIiIiP5jl8VVOWJjY6F4bXrbf//9F0OHDkVcXBwKFSqE2rVr4+DBg6hUqZIVs7RhPj7Sg4iIiIiIiAiQZjs6e1b/voQEoF494N697MWuXBn4/ffs56ZP1arSg4iIiIiIKBflmeJqdHS00e9nz56N2bNnWy4hIiIiIiIiorzi+XNgyxbjbe7fl0aKtmxpmZyIiIiIiIiswC7XXKXX7N4NVKgAeHkBgYHAjz9aOyMiIiIiIiLKa9auNTwl8OvmzTN/LkRERERERFbE4qo9q1hRuiP4yhVpXZo7d4D/+z9pjdRHj6ydHREREREREeUVL17Ia/fypXnzICIiIiIisjIWV+1V48bA5cv69z1/DpQta9l8iIiIiIiIKO9q3VpeuxYtzJsHERERERGRlbG4ao9SU4H9+423SUwEtm2zTD5ERERERESUt5UqBZQrZ7yNgwMwcqRF0iEiIiIiIrIWFlft0ezZ8tqNH2/ePIiIiIiIiMj2paZKy8ncuAFoNNmPs3074ORkeP/vvwMKfsxARERERER5G6967JHc9VSTk82bBxEREREREdmuFy+AL74AfH2BChWAMmWkJWR+/hkQRdPjlSkjFWhDQwGl8tX2atWAv/8GevTIvdyJiIiIiIhslMraCVA2dO4MzJyZdbuaNc2fCxEREREREdme1FSgXTup6Pn6aNWYGOCDD4Br14BvvzU9bkAAsGuX9LVGw5GqRERERESU7/AqyB41aQI4O2fdbtEi8+dCREREREREtmfRImDfvszTAGeMWJ0xAzh1KmevwcIqERERERHlQ7wSsldr1hjf/+GHgIuLZXIhIiIiIiIi2zJ3rvH9KhWwcKFlciEiIiIiIspDWFy1Vx07Ajt3AoUK6W53cgImT876QpqIiIiIiIjyrmvXjK+rmp4OXL5suXyIiIiIiIjyCK65as9atQKePgUePQKOHQOCgoAyZaydFREREREREVmbuzvw8qXh/QoF4OlpuXyIiIiIiIjyCI5czQu8vYH27VlYJSIiIiIiIkmfPoBSaXi/RgP07Gm5fIiIiIiIiPIIFleJiIiIiIiI8poRIwBXV/0FVpUKqFgReOsty+dFRERERERk5zgtsCUlJQHLlklT+KpUQJs2QOfO0tdERERElO8dv3ccy88tx9MXT1GyYEkMqjEIJQqWsHZaRGSPSpUCoqKAbt2Au3cBBwdpDdb0dKBWLWDjRsDRMXuxb90CliwBYmIALy9plGydOrmZPRERERERkc1iVc9Sdu0C3n4bePbs1Z3DCxYApUsDf/4JlC1r3fyIiIiIyGpepL1An/V9sPHyRqgU0p/ooihi0t5JCG8ajvFNx0MQBCtnSUR2p25dqQC6dStw9KhUYG3bFmjQAMjO7xRRBCZPBiZMkNZszYgxezbQtSuwfDng4pKLB0BERERERGR7OC2wJVy6BHTqBCQnv7pTOD1d2nfrFtCiBfD8uXVzJCKifCMiIgJ169aFu7s7fHx80LVrV1y5ciXL561ZswYVKlSAs7Mzqlatim3btlkgW6L8YdjWYdh8ZTMAIF2TjnRNOtSiGiJETNg7AQtOLLByhkSUXfv27UOnTp0QEBAAQRCwceNGyyagUkmFzylTgIkTgeDg7BVWAWDhQiA8XLquVat1r203bwaGDcu1tImIiIiIiGwVi6uWMHu2dOGp0WTep1YDt28Dq1ZZPi8iIsqX9u7di7CwMBw+fBi7du1CWloaWrdujeTkZIPPOXjwIHr37o333nsPp06dQteuXdG1a1ecP3/egpkT5U2xCbH4/ezv0Ih6/lb8zzd/fwO1Rm3BrIgotyQnJ6N69eqYM2eOtVPJGbVaGrVqiEYD/P47EBtruZyIiIiIiIisgNMCW8Lata/u5tVHoQDWrwcGDbJcTkRElG/t2LFD5/vIyEj4+PjgxIkTaNKkid7nfP/992jbti3GjBkDAJg8eTJ27dqFn376CfPnz8/UPiUlBSkpKdrvExMTc/EIiPKWrf9szbLN7cTbOPPgDGr517JARkSUm9q1a4d27drJbm+zfejZs8CdO1m327IFCAszfz5ERERERERWwpGrlvDihfH9Gg2nBSYiIqtJSEgAAHh5eRlsc+jQIYSGhupsa9OmDQ4dOqS3fUREBDw9PbWPwMDA3EuYKI95nvYcCiHrP8tfpGXxNyUR5Qk224fKuWZVKLK+/iUiIiIiIrJzLK5aQpUq0kWmIUolUK2a5fIhIiL6j0ajwciRI9GwYUNUqVLFYLu4uDj4+vrqbPP19UVcXJze9mPHjkVCQoL2cfv27VzNmygvqepTFWrR+JS/KoUK5QuXt1BGRGRNNtuHli8vrd9qjFotXf8SERERERHlYSyuWsLw4frXW82gVgPDhlkuHyIiov+EhYXh/PnzWLlyZa7GdXJygoeHh86DiPQLLR2K4p7FDY5eVQpKvFPxHXi7eVs4MyKyBpvtQ729gXfeMVxgVSiA4sWBVq0smxcREREREZGFsbhqCX37Am+/DQiC9MiQMZp1+nSgQgXr5EZERPnWxx9/jK1bt2LPnj0oVqyY0bZ+fn548OCBzrYHDx7Az8/PnCkS5QtKhRIr3l4BJ6UTVArdooVSUKKYRzHMbjvbStkREb1m9mygaFFp9qXXqVSAkxOwYkXmfURERERERHkMi6uWoFQCq1YB338PlCr1anuDBsDGjcCYMVZLjYiI8h9RFPHxxx9jw4YN2L17N0q93jcZEBwcjKioKJ1tu3btQnBwsLnSJMpXQgJDcGzoMXSv1F1bYPVw8sCI+iNwbOgx+BXgjQxEZAP8/IBjx4ARI4CMEbUqFdC9u7Q9JMS6+REREREREVlAFgumUK5RKqXpgT/+GEhMlC5A3dysnRUREeVDYWFhWL58OTZt2gR3d3ftuqmenp5wcXEBAPTv3x9FixZFREQEAGDEiBFo2rQpZs6ciQ4dOmDlypU4fvw4FixYYLXjIMprKvtUxvK3lyOyaySepT6Dp5MnlAqOACOyd8+ePcO1a9e039+8eROnT5+Gl5cXihcvbsXMssnbG5g5U5qBKSEBKFAAcHS0dlZEREREREQWw5GrliYIgKcnC6tERGQ18+bNQ0JCApo1awZ/f3/tY9WqVdo2sbGxuH//vvb7kJAQLF++HAsWLED16tWxdu1abNy4EVWqVLHGIRDlaY5KR3i5eLGwSpRHHD9+HDVr1kTNmjUBAKNGjULNmjUxfvx4K2eWQ0ol4OXFwioREREREeU7HLlKRESUz4iimGWb6OjoTNu6d++O7t27myEjIiKivKtZs2ay+l4iIiIiIiKyDxy5SkREREREREREREREREQkA4urREREREREREREREREREQysLhKRERERERERERERERERCQDi6tERERERERERERERERERDKwuEpEREREREREREREREREJAOLq0REREREREREREREREREMrC4SkRERERERERERERmN2fOHJQsWRLOzs6oX78+jh49arT9mjVrUKFCBTg7O6Nq1arYtm2bhTIlIiIyjMVVIiIiIiIiIiIiIjKrVatWYdSoUQgPD8fJkydRvXp1tGnTBg8fPtTb/uDBg+jduzfee+89nDp1Cl27dkXXrl1x/vx5C2dORESki8VVIiIiIiIiIiIiIjKrWbNmYejQoRg0aBAqVaqE+fPnw9XVFYsXL9bb/vvvv0fbtm0xZswYVKxYEZMnT0atWrXw008/WThzIiIiXSprJ2BPRFEEACQmJlo5EyIisqaMfiCjX6CssQ8lIiKAfWh2sA8lIiLA/vvQ1NRUnDhxAmPHjtVuUygUCA0NxaFDh/Q+59ChQxg1apTOtjZt2mDjxo1626ekpCAlJUX7fUJCAgD2oURE+Z05+lAWV02QlJQEAAgMDLRyJkREZAuSkpLg6elp7TTsAvtQIiJ6HftQ+diHEhHR6+y1D338+DHUajV8fX11tvv6+uLy5ct6nxMXF6e3fVxcnN72ERERmDhxYqbt7EOJiAgAnjx5kmt9KIurJggICMDt27fh7u4OQRCsnU62JCYmIjAwELdv34aHh4e108kxHo/tykvHAvB4bJ2lj0cURSQlJSEgIMDsr5VXsA+1PTwe25WXjgXg8dg69qG2j32o7eHx2K68dCwAj8fWsQ+1PWPHjtUZ6RofH48SJUogNjbWLgvS1pLX/q1aAs9Z9vC8mY7nLHsSEhJQvHhxeHl55VpMFldNoFAoUKxYMWunkSs8PDzy1D8+Ho/tykvHAvB4bJ0lj4cXZqZhH2q7eDy2Ky8dC8DjsXXsQ20X+1DbxeOxXXnpWAAej61jHypPkSJFoFQq8eDBA53tDx48gJ+fn97n+Pn5mdTeyckJTk5OmbZ7enrmqZ85S8lr/1Ytgecse3jeTMdzlj0KhSL3YuVaJCIiIiIiIiIiIiKiNzg6OqJ27dqIiorSbtNoNIiKikJwcLDe5wQHB+u0B4Bdu3YZbE9ERGQpHLlKRERERERERERERGY1atQoDBgwAHXq1EG9evXw3XffITk5GYMGDQIA9O/fH0WLFkVERAQAYMSIEWjatClmzpyJDh06YOXKlTh+/DgWLFhgzcMgIiJicTW/cXJyQnh4uN4pMuwRj8d25aVjAXg8ti6vHQ/Zprz2c8bjsV156VgAHo+ty2vHQ7Ypr/2c8XhsV146FoDHY+vy2vFYQs+ePfHo0SOMHz8ecXFxqFGjBnbs2AFfX18AQGxsrM6UjSEhIVi+fDm+/PJLjBs3DuXKlcPGjRtRpUoVWa/H9yh7eN5Mx3OWPTxvpuM5yx5znDdBFEUx16IREREREREREREREREREeVRXHOViIiIiIiIiIiIiIiIiEgGFleJiIiIiIiIiIiIiIiIiGRgcZWIiIiIiIiIiIiIiIiISAYWV4mIiIiIiIiIiIiIiIiIZGBxNQ+YM2cOSpYsCWdnZ9SvXx9Hjx412HbhwoVo3LgxChUqhEKFCiE0NDRT+4EDB0IQBJ1H27ZtzX0YAEw7lsjIyEx5Ojs767QRRRHjx4+Hv78/XFxcEBoaiqtXr5r7MLRMOZ5mzZplOh5BENChQwdtG2u+N/v27UOnTp0QEBAAQRCwcePGLJ8THR2NWrVqwcnJCWXLlkVkZGSmNqaco9xi6rGsX78erVq1gre3Nzw8PBAcHIw///xTp82ECRMyvTcVKlQw41G8YurxREdH6/1Zi4uL02lnjfcGMP149P27EAQBlStX1rax5vtDto19KPtQS2Afyj6UfSjlRexD2YdaAvtQ9qHsQykrpv7MrFmzBhUqVICzszOqVq2Kbdu2WShT25Lb/Xh+kN3fTytXroQgCOjatat5E7RRpp63+Ph4hIWFwd/fH05OTihfvny++3dq6jn77rvvEBQUBBcXFwQGBuKTTz7By5cvLZSt9Znr78WssLhq51atWoVRo0YhPDwcJ0+eRPXq1dGmTRs8fPhQb/vo6Gj07t0be/bswaFDhxAYGIjWrVvj7t27Ou3atm2L+/fvax8rVqywuWMBAA8PD508b926pbN/+vTp+OGHHzB//nwcOXIEbm5uaNOmjUV+uZh6POvXr9c5lvPnz0OpVKJ79+467azx3gBAcnIyqlevjjlz5shqf/PmTXTo0AHNmzfH6dOnMXLkSAwZMkTnYjA773luMPVY9u3bh1atWmHbtm04ceIEmjdvjk6dOuHUqVM67SpXrqzz3uzfv98c6Wdi6vFkuHLlik6+Pj4+2n3Wem8A04/n+++/1zmO27dvw8vLK9O/HWu9P2S72IeyD2Ufajr2oRL2oexD8zv2oexD2Yeajn2ohH0o+9DcZOrPzMGDB9G7d2+89957OHXqFLp27YquXbvi/PnzFs7cuszVj+dl2f39FBMTg08//RSNGze2UKa2xdTzlpqailatWiEmJgZr167FlStXsHDhQhQtWtTCmVuPqeds+fLl+PzzzxEeHo5Lly5h0aJFWLVqFcaNG2fhzK3HHH8vyiKSXatXr54YFham/V6tVosBAQFiRESErOenp6eL7u7u4tKlS7XbBgwYIHbp0iW3U82SqceyZMkS0dPT02A8jUYj+vn5id9++612W3x8vOjk5CSuWLEi1/I2JKfvzezZs0V3d3fx2bNn2m3Wem/eBEDcsGGD0Tb/+9//xMqVK+ts69mzp9imTRvt9zk9R7lBzrHoU6lSJXHixIna78PDw8Xq1avnXmLZJOd49uzZIwIQ//33X4NtbOG9EcXsvT8bNmwQBUEQY2JitNts5f0h28I+1NNgPPah5sM+lH2opbAPJXNiH+ppMB77UPNhH8o+1FLYh9oPU39mevToIXbo0EFnW/369cVhw4aZNU9bY45+PK/LzjlLT08XQ0JCxF9++cVm+lJLM/W8zZs3TyxdurSYmppqqRRtjqnnLCwsTGzRooXOtlGjRokNGzY0a562Krf+XpSDI1ftWGpqKk6cOIHQ0FDtNoVCgdDQUBw6dEhWjOfPnyMtLQ1eXl4626Ojo+Hj44OgoCB8+OGHePLkSa7m/qbsHsuzZ89QokQJBAYGokuXLrhw4YJ2382bNxEXF6cT09PTE/Xr15d9frIrN96bRYsWoVevXnBzc9PZbun3JrsOHTqkc/wA0KZNG+3x58Y5shaNRoOkpKRM/26uXr2KgIAAlC5dGn379kVsbKyVMpSnRo0a8Pf3R6tWrXDgwAHtdnt+bwDp305oaChKlCihs93e3h8yL/ah7EPZh1oH+1Dbxj6U5GAfyj6Ufah1sA+1bexDLS87PzNZ/Y7ID8zZj+dV2T1nkyZNgo+PD9577z1LpGlzsnPeNm/ejODgYISFhcHX1xdVqlTBlClToFarLZW2VWXnnIWEhODEiRPaqYNv3LiBbdu2oX379hbJ2R7lVl/A4qode/z4MdRqNXx9fXW2+/r6ZlqzwpDPPvsMAQEBOj9Mbdu2xa+//oqoqChMmzYNe/fuRbt27cz6Syw7xxIUFITFixdj06ZN+P3336HRaBASEoI7d+4AgPZ5OTk/2ZXT9+bo0aM4f/48hgwZorPdGu9NdsXFxek9/sTERLx48SJXfn6tZcaMGXj27Bl69Oih3Va/fn1ERkZix44dmDdvHm7evInGjRsjKSnJipnq5+/vj/nz52PdunVYt24dAgMD0axZM5w8eRJA7vxusZZ79+5h+/btmf7t2NP7Q5bBPpR9KPtQ62AfarvYh5Jc7EPZh7IPtQ72obaLfah1ZOdnxtDvCFv/GctN5urH87LsnLP9+/dj0aJFWLhwoSVStEnZOW83btzA2rVroVarsW3bNnz11VeYOXMmvv76a0ukbHXZOWd9+vTBpEmT0KhRIzg4OKBMmTJo1qxZvpoW2FRZ/b0olyq3EyP7MXXqVKxcuRLR0dFwdnbWbu/Vq5f266pVq6JatWooU6YMoqOj0bJlS2ukqldwcDCCg4O134eEhKBixYr4+eefMXnyZCtmlnOLFi1C1apVUa9ePZ3t9vLe5GXLly/HxIkTsWnTJp21Ydq1a6f9ulq1aqhfvz5KlCiB1atX29wdakFBQQgKCtJ+HxISguvXr2P27Nn47bffrJhZzi1duhQFCxZE165ddbbb0/tD9oF9qO1iH2q72IfaNvahZCnsQ20X+1DbxT7UtrEPpfzEUD9OryQlJaFfv35YuHAhihQpYu107IpGo4GPjw8WLFgApVKJ2rVr4+7du/j2228RHh5u7fRsUnR0NKZMmYK5c+eifv36uHbtGkaMGIHJkyfjq6++snZ6eRpHrtqxIkWKQKlU4sGDBzrbHzx4AD8/P6PPnTFjBqZOnYqdO3eiWrVqRtuWLl0aRYoUwbVr13KcsyE5OZYMDg4OqFmzpjbPjOflJGZ25eR4kpOTsXLlSll/aFvivckuPz8/vcfv4eEBFxeXXHnPLW3lypUYMmQIVq9eneXdeQULFkT58uVt8r3Rp169etpc7fG9AQBRFLF48WL069cPjo6ORtva2/tDuY99qC72obaFfah9/Y5mH0r5DftQXexDbQv7UPv6Hc0+lHIiOz8zhn5H2PLPWG6zVD+el5h6zq5fv46YmBh06tQJKpUKKpUKv/76KzZv3gyVSoXr169bKnWrys7Pmr+/P8qXLw+lUqndVrFiRcTFxSE1NdWs+dqC7Jyzr776Cv369cOQIUNQtWpVdOvWDVOmTEFERAQ0Go0l0rY7Wf29KBeLq3bM0dERtWvXRlRUlHabRqNBVFSUzp20b5o+fTomT56MHTt2oE6dOlm+zp07d/DkyRP4+/vnSt76ZPdYXqdWq3Hu3DltnqVKlYKfn59OzMTERBw5ckR2zOzKyfGsWbMGKSkpePfdd7N8HUu8N9kVHBysc/wAsGvXLu3x58Z7bkkrVqzAoEGDsGLFCnTo0CHL9s+ePcP169dt8r3R5/Tp09pc7e29ybB3715cu3ZN1gdC9vb+UO5jH6qLfahtYR9qX7+j2YdSfsM+VBf7UNvCPtS+fkezD6WcyM7PTFa/I/IDS/XjeYmp56xChQo4d+4cTp8+rX107twZzZs3x+nTpxEYGGjJ9K0mOz9rDRs2xLVr13SKgv/88w/8/f2zvIElL8jOOXv+/DkUCt0yX0ZxWhRF8yVrx3KtLxDJrq1cuVJ0cnISIyMjxYsXL4rvv/++WLBgQTEuLk4URVHs16+f+Pnnn2vbT506VXR0dBTXrl0r3r9/X/tISkoSRVEUk5KSxE8//VQ8dOiQePPmTfGvv/4Sa9WqJZYrV058+fKlTR3LxIkTxT///FO8fv26eOLECbFXr16is7OzeOHCBZ3jLViwoLhp0ybx7NmzYpcuXcRSpUqJL168MOuxZOd4MjRq1Ejs2bNnpu3WfG8yXv/UqVPiqVOnRADirFmzxFOnTom3bt0SRVEUP//8c7Ffv37a9jdu3BBdXV3FMWPGiJcuXRLnzJkjKpVKcceOHdo2WZ0jWzmWZcuWiSqVSpwzZ47Ov5v4+Hhtm9GjR4vR0dHizZs3xQMHDoihoaFikSJFxIcPH5r1WLJzPLNnzxY3btwoXr16VTx37pw4YsQIUaFQiH/99Ze2jbXem+wcT4Z3331XrF+/vt6Y1nx/yHaxD2Ufyj7U/MfCPpR9KOVN7EPZh7IPNf+xsA9lH0pZM/V33oEDB0SVSiXOmDFDvHTpkhgeHi46ODiI586ds9YhWEVu9+P5QXb71wwDBgwQu3TpYqFsbYep5y02NlZ0d3cXP/74Y/HKlSvi1q1bRR8fH/Hrr7+21iFYnKnnLDw8XHR3dxdXrFgh3rhxQ9y5c6dYpkwZsUePHtY6BIszx9+LcrC4mgf8+OOPYvHixUVHR0exXr164uHDh7X7mjZtKg4YMED7fYkSJUQAmR7h4eGiKIri8+fPxdatW4ve3t6ig4ODWKJECXHo0KEW+UPW1GMZOXKktq2vr6/Yvn178eTJkzrxNBqN+NVXX4m+vr6ik5OT2LJlS/HKlSsWORZRNO14RFEUL1++LAIQd+7cmSmWtd+bPXv26P3ZyTiGAQMGiE2bNs30nBo1aoiOjo5i6dKlxSVLlmSKa+wc2cqxNG3a1Gh7URTFnj17iv7+/qKjo6NYtGhRsWfPnuK1a9fMfizZOZ5p06aJZcqUEZ2dnUUvLy+xWbNm4u7duzPFtcZ7k53jEUVRjI+PF11cXMQFCxbojWnN94dsG/tQ9qGWwD6UfSj7UMqL2IeyD7UE9qHsQ9mHUlZM/Z23evVqsXz58qKjo6NYuXJl8Y8//rBwxrYhN/vx/MLUn7XX5dfiqiiaft4OHjwo1q9fX3RychJLly4tfvPNN2J6erqFs7YuU85ZWlqaOGHCBG0fGxgYKH700Ufiv//+a/nErcRcfy9mRRBFjg0mIiIiIiIiIiIiIiIiIsoK11wlIiIiIiIiIiIiIiIiIpKBxVUiIiIiIiIiIiIiIiIiIhlYXCUiIiIiIiIiIiIiIiIikoHFVSIiIiIiIiIiIiIiIiIiGVhcJSIiIiIiIiIiIiIiIiKSgcVVIiIiIiIiIiIiIiIiIiIZWFwlIiIiIiIiIiIiIiIiIpKBxVUiIiIiIiIiIiIiIiIiIhlYXCXKp6KjoyEIAgRBwIQJE6ydTpYycm3WrFmOYw0cOFAbLyYmJsfxIiMjtfEiIyNzHI+IiGwb+1D2oURElD3sQ9mHEhEREeUFKmsnQJTfZVxQlixZEgMHDrRqLiSJiYnRXpw2a9YsVy6kiYgo97EPtT3sQ4mI7AP7UNvDPpSIiIjIfrC4SmRlEydOBAA0bdqUF7U2IiYmRvu+AOBFLRGRjWIfanvYhxIR2Qf2obaHfSgRERGR/WBxlYjsgiiK1k6BiIjILrEPJSIiyh72oURERESkD9dcJSIiIiIiIiIiIiIiIiKSgcVVIiIiIiIiIiIiIiIiIiIZWFylfCE6OhqCIEAQBEyYMAEAcOXKFQwfPhxBQUFwc3NDoUKF0KBBA8yePRspKSmyY+/btw/vv/8+KlasiIIFC8LZ2RmBgYF4++23sW7dOoPTCGXkk2Hv3r3aba8/IiMjdZ6Xnp6OXbt24X//+x+aNm0Kf39/ODo6ws3NDSVLlkT37t2xdu1aaDQak8+TqaZNm6bNc9euXXrbXL16Ved4VqxYobfdw4cPoVAoIAgCunfvnml/xvOzWnfmxYsXmD59OurWrQtPT0+4u7ujUqVK+N///ofbt28bfW7Gz0nz5s212yZOnKj3fYmJiTEa659//sHw4cNRvnx5uLq6omDBgggODsb333+P1NRUo88lIrIl7EPNg32oYexDiSivYB9qHuxDDWMfSkRERGQZXHOV8qVVq1Zh8ODBeP78uXbb8+fPceTIERw5cgQLFizAjh07UKJECYMx4uPj0a9fP2zdujXTvjt37uDOnTtYv349mjRpgnXr1qFIkSK5knvr1q2xZ8+eTNvT0tJw69Yt3Lp1C2vXrkVISAjWr18PX1/fXHldfV6/+Nu9ezdatWqVqc3u3bszfd+7d+9M7fbs2aP9AKBFixbZyufGjRto06YNrl27prP90qVLuHTpEhYtWoQ1a9ZkK7YpfvvtNwwbNgwvXrzQbnvx4gUOHz6Mw4cPY9WqVdixYwc8PDzMngsRUW5jH5o72Ifqxz6UiPIy9qG5g32ofuxDiYiIiCyHxVXKd06cOIGpU6ciLS0Nffr0QcuWLeHi4oILFy5g8eLFuH//Pi5fvozmzZvj1KlT8PT0zBQjMTERDRs2xMWLFwEA5cqVQ/fu3VGxYkU4Ojrixo0bWLFiBc6ePYt9+/YhNDQUhw8fhrOzszbGhg0bAADdunUDAFSuXBlff/11pteqVauWzvfPnz+Hm5sbmjVrhtq1a6NUqVJwd3dHcnIyLl26hDVr1uD69es4ePAgunXrhn379kGlMs8/9dq1a8PDwwOJiYmZLl4z6Luozapddi5q4+Pj0aJFC9y6dQsAUKxYMQwePBgVK1ZEUlIStm3bho0bN+Kdd95B9erV9caoUqUKNmzYgPPnz+Orr74CAPTs2RO9evXK1NbHx0dvjB07dmDt2rVwdXVFWFgY6tatCycnJ5w+fRrz589HQkICDh06hE8//RQLFiww+TiJiKyJfWjuYR+aGftQIsrL2IfmHvahmbEPJSIiIrIwkSgf2LNnjwhA+3B1dRX37NmTqd2///4rBgcHa9sNGzZMb7xevXpp20yYMEFMT0/P1EatVoujR4/Wtvviiy/0xsrY37RpU1nHsmvXLjE5Odng/rS0NDEsLEwb97ffftPb7vVzEh4eLuu19enYsaMIQFQqlWJ8fHym/T4+PiIAMSQkRPt6MTExmdqVK1dOBCAWLVpU7+tkdZ7ef/99bZvGjRuLiYmJmdqsWbNGVCqVOj8LN2/ezNTO1HOzZMkSnZiVK1cW79y5k6ndpUuXxAIFCogARAcHBzEuLi7L2ERE1sY+NDP2oexDiYjkYB+aGftQ9qFEREREeQHXXKV8aerUqXrXTClYsCDWrFmDAgUKAAAiIyPx6NEjnTZnz57FypUrAQDvvfcewsPDoVQqM8VSKBSYMWMGGjZsCAD46aefTFpDx5DQ0FC4uroa3K9SqfDdd9+hZMmSAIClS5fm+DWNybi7V61WY+/evTr7zp8/j4cPHwIAxo8fDwcHBwCZ7xq+c+cOrl69CkB3iie5Hj16pF0TyN3dHatXr4a7u3umdu+88w4++eQTk+ObQqVSYf369ShatGimfRUqVEBYWBgAafqsv/76y6y5EBGZA/vQ3MM+VBf7UCLK69iH5h72obrYhxIRERFZFourlO8ULFgQQ4cONbi/aNGi6Nu3LwAgJSUFW7Zs0dn/+kXi//73vyxfr3///gCAhIQEHDlyJDspm0ylUqFBgwYAgKNHj2rXkDGH16dOMjT1kpubG1q0aIF69eoZbfdmPLn++OMPpKamAgD69OkDPz8/g21HjRoFhcJ8v/o6duyI8uXLG9z/+npA58+fN1seRETmwD40d7EP1cU+lIjyMvahuYt9qC72oURERESWxTVXKd9p1KiRzpoz+oSGhuLnn38GIF0UDh48WLtv3759AABnZ2dcvHhRu96NIXfv3tV+ffHiRTRp0iS7qWs9f/4cq1atwpYtW3Du3Dk8ePAAz54903vxmpiYiMTERL1r9uSGatWqoXDhwnjy5AmioqJ09mVcrDZu3BgODg5o0aIFDhw4gD179uhtB2Tvovbo0aPar1u2bGm0rb+/PypVqmS2C8rg4GCj+4sVK6b9+t9//zVLDkRE5sI+NHexD9XFPpSI8jL2obmLfagu9qFERERElsXiKuU75cqVM6nNvXv3dPbFxMQAAF6+fIlu3bqZ9NpPnz41qb0+Bw8eRK9evXD79m3ZzzHnRa0gCGjWrBnWrVuHCxcu4OHDh/Dx8YFGo9F+AJBxodq8eXNMnjwZd+/exZUrVxAUFAQA2ovc0qVLo0SJEibn8Pp7VLZs2Szbly1b1mwXtUWKFDG638nJSfv1y5cvzZIDEZG5sA/NXexDdbEPJaK8jH1o7mIfqot9KBEREZFlsbhK+Y6bm5tJbZKSknT2xcfHZ/u1M6YMyq6bN2+iTZs2ePbsGQDp4qxt27YoX748ihQpAmdnZwiCAAD44YcftBeLarU6R6+blRYtWmDdunUQRRF79uxBz549cerUKe0dsRkXtSEhIXB2dsbLly+xe/duBAUF4fr164iNjdVpZ6qM8wHA6DpAGeT8DGSXOad6IiKyNvahuY996CvsQ4koL2MfmvvYh77CPpSIiIjIslhcpXwnOTnZpDbu7u46+woUKID4+Hh4eXnhyZMnuZ6fMVOmTNFewH322WeIiIjQXsS+admyZRbLq3nz5tqvo6Ki0LNnT+0US4UKFULNmjUBSHfLhoSEYPfu3di9ezc+/PBDnamYXo9jigIFCmi/fv78eZbt5fwMEBFRZuxDcx/7UCKi/IF9aO5jH0pERERE1sJb2yjfuXbtmkltAgICdPZlrFUSHx+vc6eqJezcuRMA4OPjg2+++cbgBS0g3V1sKRUrVoS/vz+AV+vWZPy/WbNmOnfRZly4RkdHQxTFHK9zAwBFixbVfm3q+0tERPKxD8197EOJiPIH9qG5j30oEREREVkLi6uU7/z9999ISUkx2uavv/7Sfl2/fn2dfU2bNgUAaDQa/PnnnznOJ+PCVBTFLNvGxcUBAEqVKgWlUmmw3f3793HmzJkc52aKjIvV69ev4/r169i/fz+AzBeqGd8/fvwYZ8+eRXR0NADpwtjPzy9br12vXj3t169fJOtz//59XLp0yWib1y/C5bwvRET5BftQ82AfSkSU97EPNQ/2oURERERkDSyuUr4THx+PX375xeD++/fva6cycnJyQseOHXX29+/fX/v1pEmT8PLlyxzlkzGVkJwpgjLWaLl+/brRi61JkyYhPT09R3mZ6vWplKZOnaq9m/rNi9p69eppj/mnn37SXqhn925hAGjfvj0cHR0BAMuXL8eDBw8Mtv3uu++yXPvn9emdOHUTEdEr7EPNg30oEVHexz7UPNiHEhEREZE1sLhK+dJnn32Gffv2ZdqemJiIHj16ICkpCQAwaNAgeHt767SpV68eunfvDgA4e/YsunTpgkePHhl8LVEUceDAAXz66ad695cqVQoAcPnyZbx48cJo3nXr1gUg3W07c+ZMvW1mzpyJ+fPnG41jDq9flEZGRgIA/P39UalSJZ12KpUKjRs31mn35vNN5e3tjYEDBwKQ3sNevXrpnSprw4YNmDVrVpbxMt4TADh58mS28yIiyovYh+Y+9qFERPkD+9Dcxz6UiIiIiKxBZe0EiCytY8eO2LVrF1q0aIFevXqhZcuWcHFxwcWLF7Fo0SLcu3cPgHRhM23aNL0xFi1ahH/++QdnzpzBzp07UbJkSbz99tto0KABvL29kZaWhgcPHuDs2bP466+/cOfOHZQpUwYzZszIFCs0NBRnz55FcnIyOnXqhP79+8Pb21s7TVPVqlW1a7mMHDlSu97NmDFjsGfPHrRt2xa+vr6IjY3F6tWrcezYMfj7+6Nq1aratpZQunRplChRArdu3dLerfz6XcSva968ObZv365tp1Ao0KxZsxy9/rRp07Bjxw7ExsYiOjoalSpVwnvvvYcKFSogKSkJ27dvx/r161GoUCFUr15dOw2UPoUKFUKtWrVw8uRJ7NmzB8OGDUNoaCjc3d21bZo2bQoXF5cc5UxEZG/Yh5oH+1AioryPfah5sA8lIiIiIqsQifKBPXv2iABEAGJ4eLi4atUq0dXVVbvtzUdQUJB48+ZNozGTkpLEfv36iYIgGIzz+qNp06Z649y9e1f09fU1+LwlS5botJ8wYYLR1ylRooR44sQJccCAAdpt+o7lzXOSGwYOHKiTyy+//KK33fHjx3Xa1axZM8vYWZ1HURTFa9euiWXLljV4bry8vMSoqKgsz40oiuKOHTtElUplMNbrz1uyZInB9+tNN2/e1LYdMGBAlsdNRGRt7EMzHwv7UPahRERysA/NfCzsQ9mHEhEREeUFnBaY8qUePXrg5MmTCAsLQ7ly5eDq6gpPT0/Uq1cPM2fOxJkzZ1CyZEmjMQoUKIBff/0V58+fx5gxY1CvXj14e3tDpVLB1dUVJUqUQOvWrTFhwgQcOXLE4B2qAQEBOHnyJEaNGoVq1arB3d1de7ewPuHh4di9eze6du0KX19fODg4wNvbG/Xr18fUqVNx+vRp1KpVKwdnJ/venFLJ0BRLNWvWRKFChbJsZ6oyZcrg7NmzmDZtGmrVqgV3d3e4ubmhQoUK+PTTT3H69GnZr9WmTRscOnQI/fr1Q5kyZeDq6porORIR2Tv2oebBPpSIKO9jH2oe7EOJiIiIyNIEURRFaydBZG7R0dHaqYHCw8MxYcIE6yZERERkJ9iHEhERZQ/7UCIiIiKivIkjV4mIiIiIiIiIiIiIiIiIZGBxlYiIiIiIiIiIiIiIiIhIBhZXiYiIiIiIiIiIiIiIiIhkYHGViIiIiIiIiIiIiIiIiEgGFleJiIiIiIiIiIiIiIiIiGQQRFEUrZ0EEREREREREREREREREZGt48hVIiIiIiIiIiIiIiIiIiIZWFwlIiIiIiIiIiIiIiIiIpKBxVUiIiIiIiIiIiIiIiIiIhlYXCUiIiIiIiIiIiIiIiIikoHFVSIiIiIiIiIiIiIiIiIiGVhcJSIiIiIiIiIiIiIiIiKSgcVVIiIiIiIiIiIiIiIiIiIZWFwlIiIiIiIiIiIiIiIiIpLh/wE17JoKedsprgAAAABJRU5ErkJggg==",
      "text/plain": [
       "<Figure size 2300x2300 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt                                                           # 导入matplotlib.pyplot模块并简写为plt\n",
    "\n",
    "feature_name = {0: 'sepal length', 1: 'sepal width', 2: 'petal length', 3: 'petal width'} # 将不同的特征名称分别标记为0、1、2、3\n",
    "axes = plt.figure(figsize=(23, 23)).subplots(4, 4)                                        # 画出一个大小为23*23的图，包含4*4=16个子图\n",
    "\n",
    "colormap = {0: 'r', 1: 'g'}                                                               # 将标签为0的样本设为红色，标签为1的样本设为绿色\n",
    "cvalue = [colormap[i] for i in y]                                                         # 将100个样本对应的标签设置相应的颜色\n",
    "\n",
    "for i in range(4):\n",
    "    for j in range(4):\n",
    "        if i != j:\n",
    "            ax = axes[i][j]                                                               # 在[i][j]的子图上开始画图\n",
    "            ax.scatter(X[:, i], X[:, j], c=cvalue)                                        # 画出第[i]个特征和第[j]个特征组成的散点图\n",
    "            ax.set_xlabel(feature_name[i], fontsize=22)                                   # 设置X轴的名称为第[i]个特征名称，字体大小为22\n",
    "            ax.set_ylabel(feature_name[j], fontsize=22)                                   # 设置Y轴的名称为第[j]个特征名称，字体大小为22\n",
    "plt.show()                                                                                # 渲染图像，即呈现图像"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上述呈现的图像可以看到，红色的点表示标签为“0”的样本，绿色的点表示标签为“1”的样本，另外，我们发现，这两类样本的不同特征还是比较容易区分的。\n",
    "\n",
    "## 数据预处理\n",
    "\n",
    "接下来，我们需要计算生成搭建Encoder时所要用到的参数，然后将数据集划分为训练集和测试集，执行如下命令。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true,
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(100, 7)\n"
     ]
    }
   ],
   "source": [
    "alpha = X[:, :3] * X[:, 1:]           # 每一个样本中，利用相邻两个特征值计算出一个参数，即每一个样本会多出3个参数（因为有4个特征值），并储存在alpha中\n",
    "X = np.append(X, alpha, axis=1)       # 在axis=1的维度上，将alpha的数据值添加到X的特征值中\n",
    "\n",
    "print(X.shape)                        # 打印此时X的样本的数据维度"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上述打印可以看到，此时的数据集`X`中仍有100个样本，但此时每个样本却有7个特征，前4个特征值就是原来的特征值，后3个特征值就是通过上述预处理计算得到的特征值，其具体计算公式如下：\n",
    "\n",
    "$$\n",
    "X_{i+4}^{j} = X_{i}^{j} * X_{i+1}^{j}, i=0,1,2,j=1,2,...,100.\n",
    "$$\n",
    "\n",
    "最后，我们将此时的数据集分为训练集和测试集，执行如下命令。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(80, 7)\n",
      "(20, 7)\n"
     ]
    }
   ],
   "source": [
    "from sklearn.model_selection import train_test_split                                                   # 导入train_test_split函数，用于对数据集进行划分\n",
    "\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0, shuffle=True) # 将数据集划分为训练集和测试集\n",
    "\n",
    "print(X_train.shape)                                                                                   # 打印训练集中样本的数据类型\n",
    "print(X_test.shape)                                                                                    # 打印测试集中样本的数据类型"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上述打印可以看到，此时的训练集有80个样本，测试集有20个样本，每个样本均有7个特征。\n",
    "\n",
    "说明：\n",
    "\n",
    "（1）append主要用于为原始数组添加一些值，一般格式如下：np.append(arr, values, axis=None)，arr是需要被添加值的数组，values就是添加到数组arr中的值，axis表示沿着哪个方向；\n",
    "\n",
    "（2）shuffle=True表示将数据集打乱，每次都会以不同的顺序返回， shuffle就是为了避免数据投入的顺序对网络训练造成影响。增加随机性，提高网络的泛化性能，避免因为有规律的数据出现，导致权重更新时的梯度过于极端，避免最终模型过拟合或欠拟合。\n",
    "\n",
    "（3）train_test_split是交叉验证中常用的函数，主要用于是从样本中随机地按比例选取训练数据集和测试数据集，一般格式如下：\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size, random_state, shuffle=True)，其中test_size表示测试样本的比例，random_state表示产生随机数的种子，shuffle=True表示将数据集打乱。\n",
    "\n",
    "## 搭建Encoder\n",
    "\n",
    "根据图示的量子线路图，我们可以在MindSpore Quantum中搭建Encoder，将经典数据编码到量子态上。\n",
    "\n",
    "![encoder classification of iris by qnn](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/master/docs/mindquantum/docs/source_zh_cn/images/encoder_classification_of_iris_by_qnn.png)\n",
    "\n",
    "在这里，我们采用的编码方式是[IQP编码](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/nisq/mindquantum.algorithm.nisq.IQPEncoding.html)（Instantaneous Quantum Polynomial encoding），一般来说Encoder的编码方式不固定，可根据问题需要选择不同的编码方式，有时也会根据最后的性能对Encoder进行调整。\n",
    "\n",
    "Encoder中的参数$\\alpha_0,\\alpha_1,...,\\alpha_6$​​的值，就是用上述数据预处理中得到的7个特征值代入。​"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">                                 Circuit Summary                                 </span>\n",
       "╭──────────────────────┬────────────────────────────────────────────────────────╮\n",
       "│<span style=\"font-weight: bold\"> </span><span style=\"color: #3b3b95; text-decoration-color: #3b3b95; font-weight: bold\">Info</span><span style=\"font-weight: bold\">                 </span>│<span style=\"font-weight: bold\"> </span><span style=\"color: #3b3b95; text-decoration-color: #3b3b95; font-weight: bold\">value</span><span style=\"font-weight: bold\">                                                  </span>│\n",
       "├──────────────────────┼────────────────────────────────────────────────────────┤\n",
       "│ <span style=\"font-weight: bold\">Number of qubit</span>      │ 4                                                      │\n",
       "├──────────────────────┼────────────────────────────────────────────────────────┤\n",
       "│ <span style=\"font-weight: bold\">Total number of gate</span> │ 17                                                     │\n",
       "│ Barrier              │ 0                                                      │\n",
       "│ Noise Channel        │ 0                                                      │\n",
       "│ Measurement          │ 0                                                      │\n",
       "├──────────────────────┼────────────────────────────────────────────────────────┤\n",
       "│ <span style=\"font-weight: bold\">Parameter gate</span>       │ 7                                                      │\n",
       "│ 7 ansatz parameters  │ <span style=\"color: #48c9b0; text-decoration-color: #48c9b0\">alpha0, alpha1, alpha2, alpha3, alpha4, alpha5, alpha6</span> │\n",
       "╰──────────────────────┴────────────────────────────────────────────────────────╯\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1;38;2;255;0;0m                                 Circuit Summary                                 \u001b[0m\n",
       "╭──────────────────────┬────────────────────────────────────────────────────────╮\n",
       "│\u001b[1m \u001b[0m\u001b[1;38;2;59;59;149mInfo\u001b[0m\u001b[1m                \u001b[0m\u001b[1m \u001b[0m│\u001b[1m \u001b[0m\u001b[1;38;2;59;59;149mvalue\u001b[0m\u001b[1m                                                 \u001b[0m\u001b[1m \u001b[0m│\n",
       "├──────────────────────┼────────────────────────────────────────────────────────┤\n",
       "│ \u001b[1mNumber of qubit\u001b[0m      │ 4                                                      │\n",
       "├──────────────────────┼────────────────────────────────────────────────────────┤\n",
       "│ \u001b[1mTotal number of gate\u001b[0m │ 17                                                     │\n",
       "│ Barrier              │ 0                                                      │\n",
       "│ Noise Channel        │ 0                                                      │\n",
       "│ Measurement          │ 0                                                      │\n",
       "├──────────────────────┼────────────────────────────────────────────────────────┤\n",
       "│ \u001b[1mParameter gate\u001b[0m       │ 7                                                      │\n",
       "│ 7 ansatz parameters  │ \u001b[38;2;72;201;176malpha0, alpha1, alpha2, alpha3, alpha4, alpha5, alpha6\u001b[0m │\n",
       "╰──────────────────────┴────────────────────────────────────────────────────────╯\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
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      ],
      "text/plain": [
       "<mindquantum.io.display.circuit_svg_drawer.SVGCircuit at 0x7fd4c615c940>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pylint: disable=W0104\n",
    "from mindquantum.core.circuit import Circuit\n",
    "from mindquantum.core.circuit import UN\n",
    "from mindquantum.core.gates import H, X, RZ\n",
    "from mindquantum.core.parameterresolver import PRGenerator\n",
    "\n",
    "prg = PRGenerator('alpha')\n",
    "encoder = Circuit()\n",
    "encoder += UN(H, 4)                                  # H门作用在每1位量子比特\n",
    "for i in range(4):                                   # i = 0, 1, 2, 3\n",
    "    encoder += RZ(prg.new()).on(i)                 # RZ(alpha_i)门作用在第i位量子比特\n",
    "for j in range(3):                                   # j = 0, 1, 2\n",
    "    encoder += X.on(j+1, j)                          # X门作用在第j+1位量子比特，受第j位量子比特控制\n",
    "    encoder += RZ(prg.new()).on(j+1)             # RZ(alpha_{j+4})门作用在第0位量子比特\n",
    "    encoder += X.on(j+1, j)                          # X门作用在第j+1位量子比特，受第j位量子比特控制\n",
    "\n",
    "encoder = encoder.no_grad()                          # Encoder作为整个量子神经网络的第一层，不用对编码线路中的梯度求导数，因此加入no_grad()\n",
    "encoder.summary()                                    # 总结Encoder\n",
    "encoder.svg()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从对Encoder的Summary中可以看到，该量子线路由17个量子门组成，其中有7个含参量子门且参数为$\\alpha_0,\\alpha_1,...,\\alpha_6$，该量子线路调控的量子比特数为4。\n",
    "\n",
    "说明：\n",
    "\n",
    "[UN](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/circuit/mindquantum.core.circuit.UN.html)模块用于将量子门映射到不同的目标量子比特和控制量子比特，一般格式如下：`mindquantum.circuit.UN(gate, maps_obj, maps_ctrl=None)`，括号中的gate是我们需要执行的量子门，`maps_obj`是需要执行该量子门的目标量子比特，`maps_ctrl`是控制量子比特，若为`None`即无控制量子位。若每个量子比特位执行同一个非参数量子门，则可以直接写出`UN(gate, N)`，`N`表示量子比特个数。\n",
    "\n",
    "## 搭建Ansatz\n",
    "\n",
    "根据图示的量子线路图，我们可以在MindSpore Quantum中搭建Ansatz。\n",
    "\n",
    "![ansatz classification of iris by qnn](https://mindspore-website.obs.cn-north-4.myhuaweicloud.com/website-images/master/docs/mindquantum/docs/source_zh_cn/images/ansatz_classification_of_iris_by_qnn.png)\n",
    "\n",
    "与Encoder一样，Ansatz的编码方式也不固定，我们可以尝试不同的编码方式来测试最后的结果。\n",
    "\n",
    "在这里，我们采用的是 [HardwareEfficientAnsatz](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/nisq/mindquantum.algorithm.nisq.HardwareEfficientAnsatz.html)，即上述量子线路图所示的编码方式。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">                                       Circuit Summary                                       </span>\n",
       "╭──────────────────────┬────────────────────────────────────────────────────────────────────╮\n",
       "│<span style=\"font-weight: bold\"> </span><span style=\"color: #3b3b95; text-decoration-color: #3b3b95; font-weight: bold\">Info</span><span style=\"font-weight: bold\">                 </span>│<span style=\"font-weight: bold\"> </span><span style=\"color: #3b3b95; text-decoration-color: #3b3b95; font-weight: bold\">value</span><span style=\"font-weight: bold\">                                                              </span>│\n",
       "├──────────────────────┼────────────────────────────────────────────────────────────────────┤\n",
       "│ <span style=\"font-weight: bold\">Number of qubit</span>      │ 4                                                                  │\n",
       "├──────────────────────┼────────────────────────────────────────────────────────────────────┤\n",
       "│ <span style=\"font-weight: bold\">Total number of gate</span> │ 25                                                                 │\n",
       "│ Barrier              │ 0                                                                  │\n",
       "│ Noise Channel        │ 0                                                                  │\n",
       "│ Measurement          │ 0                                                                  │\n",
       "├──────────────────────┼────────────────────────────────────────────────────────────────────┤\n",
       "│ <span style=\"font-weight: bold\">Parameter gate</span>       │ 16                                                                 │\n",
       "│ 16 ansatz parameters │ <span style=\"color: #48c9b0; text-decoration-color: #48c9b0\">d0_n0_0, d0_n1_0, d0_n2_0, d0_n3_0, d1_n0_0, d1_n1_0, d1_n2_0, </span>    │\n",
       "│                      │ <span style=\"color: #48c9b0; text-decoration-color: #48c9b0\">d1_n3_0, d2_n0_0, d2_n1_0...</span>                                       │\n",
       "╰──────────────────────┴────────────────────────────────────────────────────────────────────╯\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1;38;2;255;0;0m                                       Circuit Summary                                       \u001b[0m\n",
       "╭──────────────────────┬────────────────────────────────────────────────────────────────────╮\n",
       "│\u001b[1m \u001b[0m\u001b[1;38;2;59;59;149mInfo\u001b[0m\u001b[1m                \u001b[0m\u001b[1m \u001b[0m│\u001b[1m \u001b[0m\u001b[1;38;2;59;59;149mvalue\u001b[0m\u001b[1m                                                             \u001b[0m\u001b[1m \u001b[0m│\n",
       "├──────────────────────┼────────────────────────────────────────────────────────────────────┤\n",
       "│ \u001b[1mNumber of qubit\u001b[0m      │ 4                                                                  │\n",
       "├──────────────────────┼────────────────────────────────────────────────────────────────────┤\n",
       "│ \u001b[1mTotal number of gate\u001b[0m │ 25                                                                 │\n",
       "│ Barrier              │ 0                                                                  │\n",
       "│ Noise Channel        │ 0                                                                  │\n",
       "│ Measurement          │ 0                                                                  │\n",
       "├──────────────────────┼────────────────────────────────────────────────────────────────────┤\n",
       "│ \u001b[1mParameter gate\u001b[0m       │ 16                                                                 │\n",
       "│ 16 ansatz parameters │ \u001b[38;2;72;201;176md0_n0_0, d0_n1_0, d0_n2_0, d0_n3_0, d1_n0_0, d1_n1_0, d1_n2_0, \u001b[0m    │\n",
       "│                      │ \u001b[38;2;72;201;176md1_n3_0, d2_n0_0, d2_n1_0...\u001b[0m                                       │\n",
       "╰──────────────────────┴────────────────────────────────────────────────────────────────────╯\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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width=\"80.0\" height=\"40\" rx=\"4\" ry=\"4\" stroke=\"#ffffff\" stroke-width=\"0\" fill=\"#fac209\" fill-opacity=\"1\" /><text x=\"832.8\" y=\"156.0\" font-size=\"20px\" dominant-baseline=\"middle\" text-anchor=\"middle\" font-family=\"Arial\" font-weight=\"normal\" fill=\"#ffffff\" >RY </text><text x=\"832.8\" y=\"172.0\" font-size=\"14.0px\" dominant-baseline=\"middle\" text-anchor=\"middle\" font-family=\"Arial\" font-weight=\"normal\" fill=\"#ffffff\" >d3_n2_0 </text><rect x=\"792.8\" y=\"200.0\" width=\"80.0\" height=\"40\" rx=\"4\" ry=\"4\" stroke=\"#ffffff\" stroke-width=\"0\" fill=\"#fac209\" fill-opacity=\"1\" /><text x=\"832.8\" y=\"216.0\" font-size=\"20px\" dominant-baseline=\"middle\" text-anchor=\"middle\" font-family=\"Arial\" font-weight=\"normal\" fill=\"#ffffff\" >RY </text><text x=\"832.8\" y=\"232.0\" font-size=\"14.0px\" dominant-baseline=\"middle\" text-anchor=\"middle\" font-family=\"Arial\" font-weight=\"normal\" fill=\"#ffffff\" >d3_n3_0 </text></svg>"
      ],
      "text/plain": [
       "<mindquantum.io.display.circuit_svg_drawer.SVGCircuit at 0x7fd4c6142d90>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pylint: disable=W0104\n",
    "from mindquantum.algorithm.nisq import HardwareEfficientAnsatz                                      # 导入HardwareEfficientAnsatz\n",
    "from mindquantum.core.gates import RY                                                               # 导入量子门RY\n",
    "\n",
    "ansatz = HardwareEfficientAnsatz(4, single_rot_gate_seq=[RY], entangle_gate=X, depth=3).circuit     # 通过HardwareEfficientAnsatz搭建Ansatz\n",
    "ansatz.summary()                                                                                    # 总结Ansatz\n",
    "ansatz.svg()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从对Ansatz的Summary中可以看到，该量子线路由25个量子门组成，其中有16个含参量子门且参数为d2_n3_0, d1_n1_0, d0_n2_0, d1_n0_0, d3_n2_0, d2_n2_0, d0_n1_0, d3_n1_0, d2_n0_0, d3_n0_0...，该量子线路调控的量子比特数为4。\n",
    "\n",
    "说明：\n",
    "\n",
    "[HardwareEfficientAnsatz](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/algorithm/nisq/mindquantum.algorithm.nisq.HardwareEfficientAnsatz.html)是一种容易在量子芯片上实现的Ansatz，其量子线路图由红色虚线框内的量子门组成，一般格式如下：`mindquantum.ansatz.HardwareEfficientAnsatz(n_qubits, single_rot_gate_seq, entangle_gate=X, entangle_mapping=\"linear\", depth=1)`，括号中的 `n_qubits` 表示ansatz需要作用的量子比特总数，`single_rot_gate_seq` 表示一开始每一位量子比特执行的参数门，同时后面需要执行的参数门也固定了，只是参数不同，`entangle_gate=X` 表示执行的纠缠门为X，`entangle_mapping=\"linear\"` 表示纠缠门将作用于每对相邻量子比特，`depth` 表示黑色虚线框内的量子门需要重复的次数。\n",
    "\n",
    "那么完整的量子线路就是Encoder加上Ansatz。这里我们调用量子线路的 [as_encoder](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/circuit/mindquantum.core.circuit.Circuit.html#mindquantum.core.circuit.Circuit.as_encoder) 将量子线路中的所有参数设置为编码参数，调用 [as_ansatz](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/circuit/mindquantum.core.circuit.Circuit.html#mindquantum.core.circuit.Circuit.as_ansatz) 将量子线路中的所有参数设置为待训练参数。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">                                       Circuit Summary                                       </span>\n",
       "╭──────────────────────┬────────────────────────────────────────────────────────────────────╮\n",
       "│<span style=\"font-weight: bold\"> </span><span style=\"color: #3b3b95; text-decoration-color: #3b3b95; font-weight: bold\">Info</span><span style=\"font-weight: bold\">                 </span>│<span style=\"font-weight: bold\"> </span><span style=\"color: #3b3b95; text-decoration-color: #3b3b95; font-weight: bold\">value</span><span style=\"font-weight: bold\">                                                              </span>│\n",
       "├──────────────────────┼────────────────────────────────────────────────────────────────────┤\n",
       "│ <span style=\"font-weight: bold\">Number of qubit</span>      │ 4                                                                  │\n",
       "├──────────────────────┼────────────────────────────────────────────────────────────────────┤\n",
       "│ <span style=\"font-weight: bold\">Total number of gate</span> │ 42                                                                 │\n",
       "│ Barrier              │ 0                                                                  │\n",
       "│ Noise Channel        │ 0                                                                  │\n",
       "│ Measurement          │ 0                                                                  │\n",
       "├──────────────────────┼────────────────────────────────────────────────────────────────────┤\n",
       "│ <span style=\"font-weight: bold\">Parameter gate</span>       │ 23                                                                 │\n",
       "│ 7 encoder parameters │ <span style=\"color: #ffc857; text-decoration-color: #ffc857\">alpha0, alpha1, alpha2, alpha3, alpha4, alpha5, alpha6</span>             │\n",
       "│ 16 ansatz parameters │ <span style=\"color: #48c9b0; text-decoration-color: #48c9b0\">d0_n0_0, d0_n1_0, d0_n2_0, d0_n3_0, d1_n0_0, d1_n1_0, d1_n2_0, </span>    │\n",
       "│                      │ <span style=\"color: #48c9b0; text-decoration-color: #48c9b0\">d1_n3_0, d2_n0_0, d2_n1_0...</span>                                       │\n",
       "╰──────────────────────┴────────────────────────────────────────────────────────────────────╯\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[1;38;2;255;0;0m                                       Circuit Summary                                       \u001b[0m\n",
       "╭──────────────────────┬────────────────────────────────────────────────────────────────────╮\n",
       "│\u001b[1m \u001b[0m\u001b[1;38;2;59;59;149mInfo\u001b[0m\u001b[1m                \u001b[0m\u001b[1m \u001b[0m│\u001b[1m \u001b[0m\u001b[1;38;2;59;59;149mvalue\u001b[0m\u001b[1m                                                             \u001b[0m\u001b[1m \u001b[0m│\n",
       "├──────────────────────┼────────────────────────────────────────────────────────────────────┤\n",
       "│ \u001b[1mNumber of qubit\u001b[0m      │ 4                                                                  │\n",
       "├──────────────────────┼────────────────────────────────────────────────────────────────────┤\n",
       "│ \u001b[1mTotal number of gate\u001b[0m │ 42                                                                 │\n",
       "│ Barrier              │ 0                                                                  │\n",
       "│ Noise Channel        │ 0                                                                  │\n",
       "│ Measurement          │ 0                                                                  │\n",
       "├──────────────────────┼────────────────────────────────────────────────────────────────────┤\n",
       "│ \u001b[1mParameter gate\u001b[0m       │ 23                                                                 │\n",
       "│ 7 encoder parameters │ \u001b[38;2;255;200;87malpha0, alpha1, alpha2, alpha3, alpha4, alpha5, alpha6\u001b[0m             │\n",
       "│ 16 ansatz parameters │ \u001b[38;2;72;201;176md0_n0_0, d0_n1_0, d0_n2_0, d0_n3_0, d1_n0_0, d1_n1_0, d1_n2_0, \u001b[0m    │\n",
       "│                      │ \u001b[38;2;72;201;176md1_n3_0, d2_n0_0, d2_n1_0...\u001b[0m                                       │\n",
       "╰──────────────────────┴────────────────────────────────────────────────────────────────────╯\n"
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font-weight=\"normal\" fill=\"#ffffff\" >d3_n3_0 </text></svg>"
      ],
      "text/plain": [
       "<mindquantum.io.display.circuit_svg_drawer.SVGCircuit at 0x7fd4c60de2e0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pylint: disable=W0104\n",
    "circuit = encoder.as_encoder() + ansatz.as_ansatz()                  # 完整的量子线路由Encoder和Ansatz组成\n",
    "circuit.summary()\n",
    "circuit.svg()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从对完整的量子线路的Summary中可以看到，该量子线路由42个量子门组成，其中有23个含参量子门且参数为$\\alpha_0,\\alpha_1,...,\\alpha_6$和d2_n3_0, d1_n1_0, d0_n2_0, d1_n0_0, d3_n2_0, d2_n2_0, d0_n1_0, d3_n1_0, d2_n0_0, d3_n0_0...，该量子线路调控的量子比特数为4。\n",
    "\n",
    "## 构建哈密顿量\n",
    "\n",
    "我们分别对第2位和第3位量子比特执行泡利`Z`算符测量，构建对应的[哈密顿量](https://www.mindspore.cn/mindquantum/docs/zh-CN/master/core/operators/mindquantum.core.operators.Hamiltonian.html)。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1 [Z2]\n",
      "1 [Z3]\n"
     ]
    }
   ],
   "source": [
    "from mindquantum.core.operators import QubitOperator           # 导入QubitOperator模块，用于构造泡利算符\n",
    "from mindquantum.core.operators import Hamiltonian             # 导入Hamiltonian模块，用于构建哈密顿量\n",
    "\n",
    "hams = [Hamiltonian(QubitOperator(f'Z{i}')) for i in [2, 3]]   # 分别对第2位和第3位量子比特执行泡利Z算符测量，且将系数都设为1，构建对应的哈密顿量\n",
    "for h in hams:\n",
    "    print(h)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上述打印可以看到，此时构建的哈密顿量有2个，分别为对第2位和第3位量子比特执行泡利`Z`算符，且将系数都设为1。通过泡利`Z`算符测量，我们可以得到2个哈密顿量测量值，若第1个测量值更大，则会将此样本归类到标签为“0”的类，同理，若第2个测量值更大，则会将此样本归类到标签为“1”的类。通过神经网络的训练，期望训练样本中标签为“0”的样本的第1个测量值更大，而标签为“1”的样本的第2个测量值更大，最后应用此模型来预测新样本的分类。\n",
    "\n",
    "## 搭建量子神经网络"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "MQLayer<\n",
       "  (evolution): MQOps<4 qubits mqvector VQA Operator>\n",
       "  >"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pylint: disable=W0104\n",
    "import mindspore as ms                                                                         # 导入mindspore库并简写为ms\n",
    "from mindquantum.framework import MQLayer                                                      # 导入MQLayer\n",
    "from mindquantum.simulator import Simulator\n",
    "\n",
    "ms.set_context(mode=ms.PYNATIVE_MODE, device_target=\"CPU\")\n",
    "ms.set_seed(1)                                                                                 # 设置生成随机数的种子\n",
    "sim = Simulator('mqvector', circuit.n_qubits)\n",
    "grad_ops = sim.get_expectation_with_grad(hams,\n",
    "                                         circuit,\n",
    "                                         parallel_worker=5)\n",
    "QuantumNet = MQLayer(grad_ops)          # 搭建量子神经网络\n",
    "QuantumNet"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上述打印可以看到，我们已经成功搭建了量子机器学习层，其可以无缝地跟MindSpore中其它的算子构成一张更大的机器学习网络。\n",
    "\n",
    "说明：\n",
    "\n",
    "MindSpore是一个全场景深度学习框架，旨在实现易开发、高效执行、全场景统一部署三大目标，提供支持异构加速的张量可微编程能力，支持云、服务器、边和端多种硬件平台.\n",
    "\n",
    "## 训练\n",
    "\n",
    "接下来，我们需要定义损失函数，设定需要优化的参数，然后将搭建好的量子机器学习层和MindSpore的算子组合，构成一张更大的机器学习网络，最后对该模型进行训练。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch: 1 step: 16, loss is 0.5612059831619263\n",
      "epoch: 2 step: 16, loss is 0.4522572159767151\n",
      "epoch: 3 step: 16, loss is 0.41864094138145447\n",
      "epoch: 4 step: 16, loss is 0.3906601667404175\n",
      "epoch: 5 step: 16, loss is 0.38612788915634155\n",
      "epoch: 6 step: 16, loss is 0.38768959045410156\n",
      "epoch: 7 step: 16, loss is 0.38906118273735046\n",
      "epoch: 8 step: 16, loss is 0.3899310231208801\n",
      "epoch: 9 step: 16, loss is 0.3907302916049957\n",
      "epoch: 10 step: 16, loss is 0.3917989134788513\n",
      "epoch: 11 step: 16, loss is 0.3922387659549713\n",
      "epoch: 12 step: 16, loss is 0.39297252893447876\n",
      "epoch: 13 step: 16, loss is 0.39348381757736206\n",
      "epoch: 14 step: 16, loss is 0.3938162922859192\n",
      "epoch: 15 step: 16, loss is 0.39411014318466187\n",
      "epoch: 16 step: 16, loss is 0.3943289518356323\n",
      "epoch: 17 step: 16, loss is 0.39446941018104553\n",
      "epoch: 18 step: 16, loss is 0.3945646286010742\n",
      "epoch: 19 step: 16, loss is 0.3946278691291809\n",
      "epoch: 20 step: 16, loss is 0.3946625292301178\n"
     ]
    }
   ],
   "source": [
    "from mindspore.nn import SoftmaxCrossEntropyWithLogits                         # 导入SoftmaxCrossEntropyWithLogits模块，用于定义损失函数\n",
    "from mindspore.nn import Adam                                                  # 导入Adam模块用于定义优化参数\n",
    "from mindspore.train import Accuracy, Model, LossMonitor                       # 导入Accuracy模块，用于评估预测准确率\n",
    "import mindspore as ms\n",
    "from mindspore.dataset import NumpySlicesDataset                               # 导入NumpySlicesDataset模块，用于创建模型可以识别的数据集\n",
    "\n",
    "loss = SoftmaxCrossEntropyWithLogits(sparse=True, reduction='mean')            # 通过SoftmaxCrossEntropyWithLogits定义损失函数，sparse=True表示指定标签使用稀疏格式，reduction='mean'表示损失函数的降维方法为求平均值\n",
    "opti = Adam(QuantumNet.trainable_params(), learning_rate=0.1)                  # 通过Adam优化器优化Ansatz中的参数，需要优化的是Quantumnet中可训练的参数，学习率设为0.1\n",
    "\n",
    "model = Model(QuantumNet, loss, opti, metrics={'Acc': Accuracy()})             # 建立模型：将MindSpore Quantum构建的量子机器学习层和MindSpore的算子组合，构成一张更大的机器学习网络\n",
    "\n",
    "train_loader = NumpySlicesDataset({'features': X_train, 'labels': y_train}, shuffle=False).batch(5) # 通过NumpySlicesDataset创建训练样本的数据集，shuffle=False表示不打乱数据，batch(5)表示训练集每批次样本点有5个\n",
    "test_loader = NumpySlicesDataset({'features': X_test, 'labels': y_test}).batch(5)                   # 通过NumpySlicesDataset创建测试样本的数据集，batch(5)表示测试集每批次样本点有5个\n",
    "\n",
    "\n",
    "class StepAcc(ms.Callback):                                                      # 定义一个关于每一步准确率的回调函数\n",
    "    def __init__(self, model, test_loader):\n",
    "        self.model = model\n",
    "        self.test_loader = test_loader\n",
    "        self.acc = []\n",
    "\n",
    "    def on_train_step_end(self, run_context):\n",
    "        self.acc.append(self.model.eval(self.test_loader, dataset_sink_mode=False)['Acc'])\n",
    "\n",
    "\n",
    "monitor = LossMonitor(16)                                                       # 监控训练中的损失，每16步打印一次损失值\n",
    "\n",
    "acc = StepAcc(model, test_loader)                                               # 使用建立的模型和测试样本计算预测的准确率\n",
    "\n",
    "model.train(20, train_loader, callbacks=[monitor, acc], dataset_sink_mode=False)# 将上述建立好的模型训练20次"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上述打印可以看到，20次迭代后，损失值不断下降并趋于稳定，最后收敛于约0.395。\n",
    "\n",
    "说明：\n",
    "\n",
    "（1）[nn.SoftmaxCrossEntropyWithLogits](https://www.mindspore.cn/docs/zh-CN/master/api_python/nn/mindspore.nn.SoftmaxCrossEntropyWithLogits.html#mindspore.nn.SoftmaxCrossEntropyWithLogits) 可以计算数据和标签之间的softmax交叉熵。使用交叉熵损失测量输入（使用softmax函数计算）的概率和目标之间的分布误差，其中类是互斥的（只有一个类是正的），一般格式如下：`mindspore.nn.SoftmaxCrossEntropyWithLogits(sparse=False, reduction=\"none\")`，`sparse=False` 表示指定标签是否使用稀疏格式，默认值: `False`；`reduction=\"none\"`表示适用于损失的减少类型。可选值为`\"mean\"`、`\"sum\"`和`\"none\"`。如果为`\"none\"`，则不执行减少，默认值:`\"none\"`。\n",
    "\n",
    "（2）[Adam](https://www.mindspore.cn/docs/zh-CN/master/api_python/nn/mindspore.nn.Adam.html#mindspore.nn.Adam) 模块通过自适应矩估计算法更新梯度，可以优化Ansazt中的参数，输入的是神经网络中可训练的参数；一般格式如下：`nn.Adam(net.trainable_params(), learning_rate=0.1)`，学习率可以自己调节；\n",
    "\n",
    "（3）[mindspore.train.Model](https://www.mindspore.cn/docs/zh-CN/master/api_python/train/mindspore.train.Model.html#mindspore.train.Model) 是用于训练或测试的高级 API，模型将层分组到具有训练和推理特征的对象中，一般格式如下：`mindspore.train.Model(network, loss_fn=None, optimizer=None, metrics=None, eval_network=None, eval_indexes=None, amp_level=\"O0\", acc_level=\"O0\")`，其中 `network` 就是我们要训练的网络即 `Quantumnet`；`loss_fn` 即目标函数，在这里就是定义的loss函数；`optimizer` 即优化器，用于更新权重，在这里就是定义的opti；`metrics` 就是模型在训练和测试期间需要评估的字典或一组度量，在这里就是评估准确率；\n",
    "\n",
    "（4）[Accuracy](https://www.mindspore.cn/docs/zh-CN/master/api_python/train/mindspore.train.Accuracy.html#mindspore.train.Accuracy) 用于计算分类和多标签数据的准确率，一般格式如下：`mindspore.train.Accuracy(eval_type=\"classification\")`，用于分类（单标签）和多标签（多标签分类）的数据集上计算准确率的度量，默认值：`\"classification\"`；\n",
    "\n",
    "（5）[NumpySlicesDataset](https://www.mindspore.cn/docs/zh-CN/master/api_python/dataset/mindspore.dataset.NumpySlicesDataset.html#mindspore.dataset.NumpySlicesDataset) 使用给定的数据切片创建数据集，主要用于将Python数据加载到数据集中，一般格式如下：`mindspore.dataset.NumpySlicesDataset(data, column_names=None, num_samples=None, num_parallel_workers=1, shuffle=None, sampler=None, num_shards=None, shard_id=None)`；\n",
    "\n",
    "（6）[Callback](https://www.mindspore.cn/docs/zh-CN/master/api_python/train/mindspore.train.Callback.html#mindspore.train.Callback) 用于构建回调类的抽象基类，回调是上下文管理器，在传递到模型时将输入和输出。你可以使用此机制自动初始化和释放资源。回调函数将执行当前步骤或数据轮回中的一些操作；\n",
    "\n",
    "（7）[LossMonitor](https://www.mindspore.cn/docs/zh-CN/master/api_python/train/mindspore.train.LossMonitor.html#mindspore.train.LossMonitor) 主要用于监控训练中的损失，如果损失是NAN或INF，它将终止训练，一般格式如下：`mindspore.train.LossMonitor(per_print_times=1)`，`per_print_times=1`表示每秒钟打印一次损失，默认值：`1`；\n",
    "\n",
    "（8）[train](https://www.mindspore.cn/docs/zh-CN/master/api_python/train/mindspore.train.Model.html#mindspore.train.Model.train) 方法用于训练模型，其中迭代由Python前端控制；当设置PyNative模式或CPU时，训练过程将在数据集不接收的情况下执行，一般格式如下：`train(epoch, train_dataset, callbacks=None, dataset_sink_mode=True, sink_size=-1)`，其中`epoch`表示在数据上的总迭代次数；`train_dataset`就是我们定义的`train_loader`；`callbacks`就是我们需要回调的损失值和准确率；`dataset_sink_mode`表示确定是否通过数据集通道传递数据，文档中为`False`。\n",
    "\n",
    "## 训练过程中的准确率\n",
    "\n",
    "我们已经看到损失值趋于稳定，那么我们还可以将模型在训练过程中的预测的准确率呈现出来，执行如下代码。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Accuracy')"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(acc.acc)\n",
    "plt.title('Statistics of accuracy', fontsize=20)\n",
    "plt.xlabel('Steps', fontsize=20)\n",
    "plt.ylabel('Accuracy', fontsize=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上述打印的图像可以看到，在大约50步后，预测的准确率收敛于1，也就是说预测的准确率已经可以达到100%。\n",
    "\n",
    "## 预测\n",
    "\n",
    "最后，我们测试一下训练好的模型，将其应用在测试集上。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "预测分类结果： [0 1 0 1 1 1 0 1 1 1 1 1 1 0 0 0 0 0 0 0]\n",
      "实际分类结果： [0 1 0 1 1 1 0 1 1 1 1 1 1 0 0 0 0 0 0 0]\n",
      "{'Acc': 1.0}\n"
     ]
    }
   ],
   "source": [
    "from mindspore import ops                                         # 导入ops模块\n",
    "\n",
    "predict = np.argmax(ops.Softmax()(model.predict(ms.Tensor(X_test))), axis=1)    # 使用建立的模型和测试样本，得到测试样本预测的分类\n",
    "correct = model.eval(test_loader, dataset_sink_mode=False)                   # 计算测试样本应用训练好的模型的预测准确率\n",
    "\n",
    "print(\"预测分类结果：\", predict)                                              # 对于测试样本，打印预测分类结果\n",
    "print(\"实际分类结果：\", y_test)                                               # 对于测试样本，打印实际分类结果\n",
    "\n",
    "print(correct)                                                               # 打印模型预测的准确率"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上述打印的可以看到，预测分类结果和实际分类结果完全一致，模型预测的准确率达到了100%。\n",
    "\n",
    "至此，我们体验了如何通过搭建量子神经网络来解决经典机器学习中的经典问题——鸢尾花分类问题。相信大家也对使用MindSpore Quantum有了更进一步的了解！期待大家挖掘更多的问题，充分发挥MindSpore Quantum强大的功能！"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "<table border=\"1\">\n",
       "  <tr>\n",
       "    <th>Software</th>\n",
       "    <th>Version</th>\n",
       "  </tr>\n",
       "<tr><td>mindquantum</td><td>0.9.11</td></tr>\n",
       "<tr><td>scipy</td><td>1.10.1</td></tr>\n",
       "<tr><td>numpy</td><td>1.23.5</td></tr>\n",
       "<tr>\n",
       "    <th>System</th>\n",
       "    <th>Info</th>\n",
       "</tr>\n",
       "<tr><td>Python</td><td>3.9.16</td></tr><tr><td>OS</td><td>Linux x86_64</td></tr><tr><td>Memory</td><td>8.3 GB</td></tr><tr><td>CPU Max Thread</td><td>8</td></tr><tr><td>Date</td><td>Sun Dec 31 00:46:47 2023</td></tr>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<mindquantum.utils.show_info.InfoTable at 0x7fd52cf22ca0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from mindquantum.utils.show_info import InfoTable\n",
    "\n",
    "InfoTable('mindquantum', 'scipy', 'numpy')"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.19"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
